Installed R Statistical Software Packages (Ubuntu 20.04)
This table lists all R pre-installed packages that are immediately available in every CoCalc project running on the default "Ubuntu 20.04" image, along with their version numbers. If something is missing, you can install it yourself, or request that we install them.
Learn more about R functionality in CoCalc.
Available Environments
- R Project:
The "official" R distribution from the R Project, installed system-wide.
R version 4.2.3 (2023-03-15) -- "Shortstop Beagle" Copyright (C) 2023 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu (64-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under the terms of the GNU General Public License versions 2 or 3. For more information about these matters see https://www.gnu.org/licenses/.- SageMath's R:
R distribution within SageMath. Start via
R-sageor select the appropriate kernel.R version 4.2.3 (2023-03-15) -- "Shortstop Beagle" Copyright (C) 2023 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu (64-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under the terms of the GNU General Public License versions 2 or 3. For more information about these matters see https://www.gnu.org/licenses/.
Showing 4639 libraries
| Library | R Project | SageMath's R |
|---|---|---|
abbyyR Access to Abbyy Optical Character Recognition (OCR) API | 0.5.5 | 0.5.5 |
abc Tools for Approximate Bayesian Computation (ABC) | 2.2.1 | 2.2.1 |
abc.data Data Only: Tools for Approximate Bayesian Computation (ABC) | 1.0 | 1.0 |
ABCoptim Implementation of Artificial Bee Colony (ABC) Optimization | 0.15.0 | 0.15.0 |
abind Combine Multidimensional Arrays | 1.4-5 | 1.4-5 |
abn Modelling Multivariate Data with Additive Bayesian Networks | 2.7-3 | 2.7-3 |
acc Exploring Accelerometer Data | 1.3.3 | 1.3.3 |
accelerometry Functions for Processing Accelerometer Data | 3.1.2 | 3.1.2 |
accelmissing Missing Value Imputation for Accelerometer Data | 1.4 | 1.4 |
acepack ACE and AVAS for Selecting Multiple Regression Transformations | 1.4.1 | 1.4.1 |
acp Autoregressive Conditional Poisson | 2.1 | 2.1 |
acs Download, Manipulate, and Present American Community Survey and Decennial Data from the US Census | 2.1.4 | 2.1.4 |
ACSWR A Companion Package for the Book "A Course in Statistics with R" | 1.0 | 1.0 |
ActCR Extract Circadian Rhythms Metrics from Actigraphy Data | 0.3.0 | 0.3.0 |
actuar Actuarial Functions and Heavy Tailed Distributions | 3.3-2 | 3.3-2 |
adabag Applies Multiclass AdaBoost.M1, SAMME and Bagging | 4.2 | 4.2 |
adagio Discrete and Global Optimization Routines | 0.8.5 | 0.8.5 |
AdapEnetClass A Class of Adaptive Elastic Net Methods for Censored Data | 1.2 | 1.2 |
adapr Implementation of an Accountable Data Analysis Process | 2.0.0 | 2.0.0 |
adaptivetau Tau-Leaping Stochastic Simulation | 2.2-3 | 2.2-3 |
adaptMT Adaptive P-Value Thresholding for Multiple Hypothesis Testing with Side Information | 1.0.0 | 1.0.0 |
adaptsmoFMRI Adaptive Smoothing of FMRI Data | 1.2 | 1.2 |
adaptTest Adaptive Two-Stage Tests | 1.1 | 1.1 |
AdaSampling Adaptive Sampling for Positive Unlabeled and Label Noise Learning | 1.3 | 1.3 |
addhazard Fit Additive Hazards Models for Survival Analysis | 1.1.0 | 1.1.0 |
additivityTests Additivity Tests in the Two Way Anova with Single Sub-Class Numbers | 1.1-4.1 | 1.1-4.1 |
ade4 Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences | 1.7-22 | 1.7-22 |
adegenet Exploratory Analysis of Genetic and Genomic Data | 2.1.10 | 2.1.10 |
adegraphics An S4 Lattice-Based Package for the Representation of Multivariate Data | 1.0-18 | 1.0-18 |
adehabitatHR Home Range Estimation | 0.4.20 | 0.4.20 |
adehabitatHS Analysis of Habitat Selection by Animals | 0.3.16 | 0.3.16 |
adehabitatLT Analysis of Animal Movements | 0.3.26 | 0.3.26 |
adehabitatMA Tools to Deal with Raster Maps | 0.3.15 | 0.3.15 |
adephylo Exploratory Analyses for the Phylogenetic Comparative Method | 1.1-11 | 1.1-11 |
AdequacyModel Adequacy of Probabilistic Models and General Purpose Optimization | 2.0.0 | 2.0.0 |
ADGofTest Anderson-Darling GoF test | 0.3 | 0.3 |
adhoc Calculate Ad Hoc Distance Thresholds for DNA Barcoding Identification | 1.1 | 1.1 |
adimpro Adaptive Smoothing of Digital Images | 0.9.5 | 0.9.5 |
adiv Analysis of Diversity | 2.1.1 | 2.1.1 |
admisc Adrian Dusa's Miscellaneous | 0.27 | 0.27 |
AdMit Adaptive Mixture of Student-t Distributions | 2.1.9 | 2.1.9 |
ADPclust Fast Clustering Using Adaptive Density Peak Detection | 0.7 | 0.7 |
ADPF Use Least Squares Polynomial Regression and Statistical Testing to Improve Savitzky-Golay | 0.0.1 | 0.0.1 |
ads Spatial Point Patterns Analysis | 1.5-5 | 1.5-5 |
AER Applied Econometrics with R | 1.2-10 | 1.2-10 |
affxparser | 1.68.1 | 1.68.1 |
affy | 1.74.0 | 1.74.0 |
affydata | 1.44.0 | 1.44.0 |
affyio | 1.66.0 | 1.66.0 |
affyPLM | 1.72.0 | 1.72.0 |
aggregation p-Value Aggregation Methods | 1.0.1 | 1.0.1 |
agricolae Statistical Procedures for Agricultural Research | 1.3-5 | 1.3-5 |
AGSDest Estimation in Adaptive Group Sequential Trials | 2.3.4 | 2.3.4 |
ahaz Regularization for Semiparametric Additive Hazards Regression | 1.15 | 1.15 |
AIM AIM: adaptive index model | 1.01 | 1.01 |
airGR Suite of GR Hydrological Models for Precipitation-Runoff Modelling | 1.7.0 | 1.7.0 |
airGRteaching Teaching Hydrological Modelling with the GR Rainfall-Runoff Models ('Shiny' Interface Included) | 0.2.13 | 0.2.13 |
airports Data on Airports | 0.1.0 | 0.1.0 |
akima Interpolation of Irregularly and Regularly Spaced Data | 0.6-3.4 | 0.6-3.4 |
alabama Constrained Nonlinear Optimization | 2022.4-1 | 2022.4-1 |
ald The Asymmetric Laplace Distribution | 1.3.1 | 1.3.1 |
AlgDesign Algorithmic Experimental Design | 1.2.1 | 1.2.1 |
alineR Alignment of Phonetic Sequences Using the 'ALINE' Algorithm | 1.1.4 | 1.1.4 |
alleHap Allele Imputation and Haplotype Reconstruction from Pedigree Databases | 0.9.9 | 0.9.9 |
alluvial Alluvial Diagrams | 0.1-2 | 0.1-2 |
alpaca Fit GLM's with High-Dimensional k-Way Fixed Effects | 0.3.4 | 0.3.4 |
alphahull Generalization of the Convex Hull of a Sample of Points in the Plane | 2.4 | 2.4 |
alphavantager Lightweight R Interface to the Alpha Vantage API | 0.1.2 | 0.1.2 |
ALS Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) | 0.0.7 | 0.0.7 |
altmeta Alternative Meta-Analysis Methods | 4.0 | 4.0 |
amap Another Multidimensional Analysis Package | 0.8-19 | 0.8-19 |
Amelia A Program for Missing Data | 1.8.1 | 1.8.1 |
AmericanCallOpt This package includes pricing function for selected American<U+000a>call options with underlying assets that generate payouts. | 0.95 | 0.95 |
AMORE Artificial Neural Network Training and Simulating | 0.2-16 | 0.2-16 |
amt Animal Movement Tools | 0.1.1 | 0.1.1 |
anacor Simple and Canonical Correspondence Analysis | 1.1-4 | 1.1-4 |
analogsea Interface to 'Digital Ocean' | 1.0.6 | 1.0.6 |
analogue Analogue and Weighted Averaging Methods for Palaeoecology | 0.17-6 | 0.17-6 |
AnalyzeFMRI Functions for Analysis of fMRI Datasets Stored in the ANALYZE or NIFTI Format | 1.1-24 | 1.1-24 |
anesrake ANES Raking Implementation | 0.80 | 0.80 |
animalTrack Animal track reconstruction for high frequency 2-dimensional<U+000a>(2D) or 3-dimensional (3D) movement data. | 1.0.0 | 1.0.0 |
animation A Gallery of Animations in Statistics and Utilities to Create Animations | 2.7 | 2.7 |
anipaths Animation of Multiple Trajectories with Uncertainty | 0.9.8 | 0.9.8 |
anMC Compute High Dimensional Orthant Probabilities | 0.2.3 | 0.2.3 |
annotate | 1.74.0 | 1.74.0 |
AnnotationDbi | 1.58.0 | 1.58.0 |
AnnotationFilter | 1.20.0 | 1.20.0 |
AnnotationHub | 3.4.0 | 3.4.0 |
anomalize Tidy Anomaly Detection | 0.2.2 | 0.2.2 |
anomaly Detecting Anomalies in Data | 4.0.2 | 4.0.2 |
antitrust Tools for Antitrust Practitioners | 0.99.25 | 0.99.25 |
anyLib Install and Load Any Package from CRAN, Bioconductor or Github | 1.0.5 | 1.0.5 |
anytime Anything to 'POSIXct' or 'Date' Converter | 0.3.9 | 0.3.9 |
aod Analysis of Overdispersed Data | 1.3.2 | 1.3.2 |
aoos Another Object Orientation System | 0.5.0 | 0.5.0 |
apcluster Affinity Propagation Clustering | 1.4.10 | 1.4.10 |
ape Analyses of Phylogenetics and Evolution | 5.6-2 | 5.6-2 |
apex Phylogenetic Methods for Multiple Gene Data | 1.0.4 | 1.0.4 |
aphid Analysis with Profile Hidden Markov Models | 1.3.5 | 1.3.5 |
aplore3 Datasets from Hosmer, Lemeshow and Sturdivant, "Applied Logistic Regression" (3rd Ed., 2013) | 0.9 | 0.9 |
aplpack Another Plot Package: 'Bagplots', 'Iconplots', 'Summaryplots', Slider Functions and Others | 1.3.5 | 1.3.5 |
apollo Tools for Choice Model Estimation and Application | 0.2.8 | 0.2.8 |
AppliedPredictiveModeling Functions and Data Sets for 'Applied Predictive Modeling' | 1.1-7 | 1.1-7 |
approximator Bayesian Prediction of Complex Computer Codes | 1.2-7 | 1.2-7 |
aprof Amdahl's Profiler, Directed Optimization Made Easy | 0.4.1 | 0.4.1 |
APSIM General Utility Functions for the 'Agricultural Production Systems Simulator' | 0.9.3 | 0.9.3 |
apsrtable apsrtable model-output formatter for social science | 0.8-8 | 0.8-8 |
apt Asymmetric Price Transmission | 3.0 | 3.0 |
APtools Average Positive Predictive Values (AP) for Binary Outcomes and Censored Event Times | 6.8.8 | 6.8.8 |
apTreeshape Analyses of Phylogenetic Treeshape | 1.5-0.1 | 1.5-0.1 |
aqp Algorithms for Quantitative Pedology | 1.42 | 1.42 |
AquaEnv Integrated Development Toolbox for Aquatic Chemical Model Generation | 1.0-4 | 1.0-4 |
ARCensReg Fitting Univariate Censored Linear Regression Model with Autoregressive Errors | 2.1 | 2.1 |
archivist Tools for Storing, Restoring and Searching for R Objects | 2.3.6 | 2.3.6 |
ArDec Time Series Autoregressive-Based Decomposition | 2.1-1 | 2.1-1 |
areal Areal Weighted Interpolation | 0.1.7 | 0.1.7 |
arfima Fractional ARIMA (and Other Long Memory) Time Series Modeling | 1.8-1 | 1.8-1 |
argosfilter Argos Locations Filter | 0.63 | 0.63 |
aricode Efficient Computations of Standard Clustering Comparison Measures | 1.0.0 | 1.0.0 |
arm Data Analysis Using Regression and Multilevel/Hierarchical Models | 1.13-1 | 1.13-1 |
AROC Covariate-Adjusted Receiver Operating Characteristic Curve Inference | 1.0-4 | 1.0-4 |
arpr Advanced R Pipes | 0.1.2 | 0.1.2 |
arrangements Fast Generators and Iterators for Permutations, Combinations, Integer Partitions and Compositions | 1.1.9 | 1.1.9 |
ars Adaptive Rejection Sampling | 0.6 | 0.6 |
arsenal An Arsenal of 'R' Functions for Large-Scale Statistical Summaries | 3.6.3 | 3.6.3 |
arules Mining Association Rules and Frequent Itemsets | 1.7-6 | 1.7-6 |
arulesCBA Classification Based on Association Rules | 1.2.5 | 1.2.5 |
aRxiv Interface to the arXiv API | 0.6 | 0.6 |
asaur Data Sets for "Applied Survival Analysis Using R"" | 0.50 | 0.50 |
asbio A Collection of Statistical Tools for Biologists | 1.8-4 | 1.8-4 |
asd Simulations for Adaptive Seamless Designs | 2.2 | 2.2 |
ASGS.foyer Interface to the Australian Statistical Geography Standard | 0.3.1 | 0.3.1 |
ash David Scott's ASH Routines | 1.0-15 | 1.0-15 |
AsioHeaders 'Asio' C++ Header Files | 1.22.1-2 | 1.22.1-2 |
askpass Safe Password Entry for R, Git, and SSH | 1.1 | 1.1 |
aspace A collection of functions for estimating centrographic<U+000a>statistics and computational geometries for spatial point<U+000a>patterns | 3.2 | 3.2 |
aspect A General Framework for Multivariate Analysis with Optimal Scaling | 1.0-6 | 1.0-6 |
assertive Readable Check Functions to Ensure Code Integrity | 0.3-6 | 0.3-6 |
assertive.base A Lightweight Core of the 'assertive' Package | 0.0-9 | 0.0-9 |
assertive.code Assertions to Check Properties of Code | 0.0-3 | 0.0-3 |
assertive.data Assertions to Check Properties of Data | 0.0-3 | 0.0-3 |
assertive.data.uk Assertions to Check Properties of Strings | 0.0-2 | 0.0-2 |
assertive.data.us Assertions to Check Properties of Strings | 0.0-2 | 0.0-2 |
assertive.datetimes Assertions to Check Properties of Dates and Times | 0.0-3 | 0.0-3 |
assertive.files Assertions to Check Properties of Files | 0.0-2 | 0.0-2 |
assertive.matrices Assertions to Check Properties of Matrices | 0.0-2 | 0.0-2 |
assertive.models Assertions to Check Properties of Models | 0.0-2 | 0.0-2 |
assertive.numbers Assertions to Check Properties of Numbers | 0.0-2 | 0.0-2 |
assertive.properties Assertions to Check Properties of Variables | 0.0-5 | 0.0-5 |
assertive.reflection Assertions for Checking the State of R | 0.0-5 | 0.0-5 |
assertive.sets Assertions to Check Properties of Sets | 0.0-3 | 0.0-3 |
assertive.strings Assertions to Check Properties of Strings | 0.0-3 | 0.0-3 |
assertive.types Assertions to Check Types of Variables | 0.0-3 | 0.0-3 |
assertthat Easy Pre and Post Assertions | 0.2.1 | 0.2.1 |
aster Aster Models | 1.1-2 | 1.1-2 |
aster2 Aster Models | 0.3 | 0.3 |
astrochron A Computational Tool for Astrochronology | 1.1 | 1.1 |
astrodatR Astronomical Data | 0.1 | 0.1 |
astroFns Astronomy: Time and Position Functions, Misc. Utilities | 4.2-1 | 4.2-1 |
astrolibR Astronomy Users Library | 0.1 | 0.1 |
astsa Applied Statistical Time Series Analysis | 2.0 | 2.0 |
asymmetry Multidimensional Scaling of Asymmetric Proximities | 2.0.4 | 2.0.4 |
asypow Calculate Power Utilizing Asymptotic Likelihood Ratio Methods | 2015.6.25 | 2015.6.25 |
AtelieR A GTK GUI for teaching basic concepts in statistical inference,<U+000a>and doing elementary bayesian tests. | 0.24 | 0.24 |
ath1121501.db | 3.13.0 | 3.13.0 |
ath1121501cdf | 2.18.0 | 2.18.0 |
ATmet Advanced Tools for Metrology | 1.2.1 | 1.2.1 |
AtmRay Acoustic Traveltime Calculations for 1-D Atmospheric Models | 1.31 | 1.31 |
atom4R Tools to Handle and Publish Metadata as 'Atom' XML Format | 0.2 | 0.2 |
aTSA Alternative Time Series Analysis | 3.1.2 | 3.1.2 |
attempt Tools for Defensive Programming | 0.3.1 | 0.3.1 |
aurelius Generates PFA Documents from R Code and Optionally Runs Them | 0.8.4 | 0.8.4 |
automap Automatic Interpolation Package | 1.1-1 | 1.1-1 |
av Working with Audio and Video in R | 0.8.3 | 0.8.3 |
AWAPer Catchment Area Weighted Climate Data Anywhere in Australia | 0.1.46 | 0.1.46 |
aws Adaptive Weights Smoothing | 2.5-1 | 2.5-1 |
aws.signature Amazon Web Services Request Signatures | 0.6.0 | 0.6.0 |
awsMethods Class and Methods Definitions for Packages 'aws', 'adimpro', 'fmri', 'dwi' | 1.1-1 | 1.1-1 |
AzureAuth Authentication Services for Azure Active Directory | 1.3.3 | 1.3.3 |
AzureContainers Interface to 'Container Instances', 'Docker Registry' and 'Kubernetes' in 'Azure' | 1.3.2 | 1.3.2 |
AzureGraph Simple Interface to 'Microsoft Graph' | 1.3.2 | 1.3.2 |
AzureRMR Interface to 'Azure Resource Manager' | 2.4.3 | 2.4.3 |
AzureStor Storage Management in 'Azure' | 3.7.0 | 3.7.0 |
AzureVM Virtual Machines in 'Azure' | 2.2.2 | 2.2.2 |
BaBooN Bayesian Bootstrap Predictive Mean Matching - Multiple and Single Imputation for Discrete Data | 0.2-0 | 0.2-0 |
BACCO Bayesian Analysis of Computer Code Output (BACCO) | 2.0-9 | 2.0-9 |
backports Reimplementations of Functions Introduced Since R-3.0.0 | 1.4.1 | 1.4.1 |
backtest Exploring Portfolio-Based Conjectures About Financial Instruments | 0.3-4 | 0.3-4 |
bain Bayes Factors for Informative Hypotheses | 0.2.8 | 0.2.8 |
BalancedSampling Balanced and Spatially Balanced Sampling | 1.6.3 | 1.6.3 |
BaM Functions and Datasets for "Bayesian Methods: A Social and Behavioral Sciences Approach" | 1.0.2 | 1.0.2 |
bamdit Bayesian Meta-Analysis of Diagnostic Test Data | 3.4.0 | 3.4.0 |
bamlss Bayesian Additive Models for Location, Scale, and Shape (and Beyond) | 1.1-9 | 1.1-9 |
BAMMtools Analysis and Visualization of Macroevolutionary Dynamics on Phylogenetic Trees | 2.1.10 | 2.1.10 |
banR R Client for the BAN API | 0.2.2 | 0.2.2 |
barsurf Contour Plots, 3D Plots, Vector Fields and Heatmaps | 0.7.0 | 0.7.0 |
BART Bayesian Additive Regression Trees | 2.9.3 | 2.9.3 |
bartMachine Bayesian Additive Regression Trees | 1.3.3.1 | 1.3.3.1 |
bartMachineJARs bartMachine JARs | 1.2.1 | 1.2.1 |
base | 4.2.3 | 4.2.3 |
base64 Base64 Encoder and Decoder | 2.0.1 | 2.0.1 |
base64enc Tools for base64 encoding | 0.1-3 | 0.1-3 |
base64url Fast and URL-Safe Base64 Encoder and Decoder | 1.4 | 1.4 |
basefun Infrastructure for Computing with Basis Functions | 1.1-3 | 1.1-3 |
baseline Baseline Correction of Spectra | 1.3-4 | 1.3-4 |
BaSTA Age-Specific Survival Analysis from Incomplete Capture-Recapture/Recovery Data | 1.9.5 | 1.9.5 |
batch Batching Routines in Parallel and Passing Command-Line Arguments to R | 1.1-5 | 1.1-5 |
BatchExperiments Statistical Experiments on Batch Computing Clusters | 1.4.3 | 1.4.3 |
BatchJobs Batch Computing with R | 1.9 | 1.9 |
batchmeans Consistent Batch Means Estimation of Monte Carlo Standard Errors | 1.0-4 | 1.0-4 |
batchtools Tools for Computation on Batch Systems | 0.9.16 | 0.9.16 |
BayesCombo Bayesian Evidence Combination | 1.0 | 1.0 |
BayesDA Functions and Datasets for the book "Bayesian Data Analysis" | 2012.04-1 | 2012.04-1 |
BayesFactor Computation of Bayes Factors for Common Designs | 0.9.12-4.4 | 0.9.12-4.4 |
BayesFM Bayesian Inference for Factor Modeling | 0.1.5 | 0.1.5 |
bayesGARCH Bayesian Estimation of the GARCH(1,1) Model with Student-t Innovations | 2.1.10 | 2.1.10 |
BayesianAnimalTracker Bayesian Melding of GPS and DR Path for Animal Tracking | 1.2 | 1.2 |
bayesImageS Bayesian Methods for Image Segmentation using a Potts Model | 0.6-1 | 0.6-1 |
BayesLCA Bayesian Latent Class Analysis | 1.9 | 1.9 |
bayesm Bayesian Inference for Marketing/Micro-Econometrics | 3.1-5 | 3.1-5 |
bayesmeta Bayesian Random-Effects Meta-Analysis and Meta-Regression | 3.2 | 3.2 |
bayesmix Bayesian Mixture Models with JAGS | 0.7-5 | 0.7-5 |
BayesPiecewiseICAR Hierarchical Bayesian Model for a Hazard Function | 0.2.1 | 0.2.1 |
bayesplot Plotting for Bayesian Models | 1.10.0 | 1.10.0 |
bayesQR Bayesian Quantile Regression | 2.3 | 2.3 |
BayesSAE Bayesian Analysis of Small Area Estimation | 1.0-2 | 1.0-2 |
BayesSummaryStatLM MCMC Sampling of Bayesian Linear Models via Summary Statistics | 2.0 | 2.0 |
bayestestR Understand and Describe Bayesian Models and Posterior Distributions | 0.13.0 | 0.13.0 |
BayesTree Bayesian Additive Regression Trees | 0.3-1.4 | 0.3-1.4 |
BayesValidate BayesValidate Package | 0.0 | 0.0 |
BayesVarSel Bayes Factors, Model Choice and Variable Selection in Linear Models | 2.2.5 | 2.2.5 |
BayesX R Utilities Accompanying the Software Package BayesX | 0.3-1.1 | 0.3-1.1 |
BayesXsrc Distribution of the 'BayesX' C++ Sources | 3.0-2 | 3.0-2 |
BayHaz R Functions for Bayesian Hazard Rate Estimation | 0.1-3 | 0.1-3 |
BaylorEdPsych R Package for Baylor University Educational Psychology<U+000a>Quantitative Courses | 0.5 | 0.5 |
BAYSTAR On Bayesian Analysis of Threshold Autoregressive Models | 0.2-10 | 0.2-10 |
bazar Miscellaneous Basic Functions | 1.0.11 | 1.0.11 |
BB Solving and Optimizing Large-Scale Nonlinear Systems | 2019.10-1 | 2019.10-1 |
bbemkr Bayesian bandwidth estimation for multivariate kernel regression<U+000a>with Gaussian error | 2.0 | 2.0 |
BBmisc Miscellaneous Helper Functions for B. Bischl | 1.12 | 1.12 |
bbmle Tools for General Maximum Likelihood Estimation | 1.0.25 | 1.0.25 |
BBMM Brownian bridge movement model | 3.0 | 3.0 |
BCBCSF Bias-Corrected Bayesian Classification with Selected Features | 1.0-1 | 1.0-1 |
BCC1997 Calculation of Option Prices Based on a Universal Solution | 0.1.1 | 0.1.1 |
BCE Bayesian Composition Estimator: Estimating Sample (Taxonomic) Composition from Biomarker Data | 2.2.0 | 2.2.0 |
BCEA Bayesian Cost Effectiveness Analysis | 2.4.2 | 2.4.2 |
Bchron Radiocarbon Dating, Age-Depth Modelling, Relative Sea Level Rate Estimation, and Non-Parametric Phase Modelling | 4.7.6 | 4.7.6 |
bcp Bayesian Analysis of Change Point Problems | 4.0.3 | 4.0.3 |
bcpa Behavioral Change Point Analysis of Animal Movement | 1.1 | 1.1 |
bcrm Bayesian Continual Reassessment Method for Phase I Dose-Escalation Trials | 0.5.4 | 0.5.4 |
BDgraph Bayesian Structure Learning in Graphical Models using Birth-Death MCMC | 2.70 | 2.70 |
bdsmatrix Routines for Block Diagonal Symmetric Matrices | 1.3-6 | 1.3-6 |
beachmat | 2.12.0 | 2.12.0 |
beadarray | 2.46.0 | 2.46.0 |
BeadDataPackR | 1.48.0 | 1.48.0 |
beeswarm The Bee Swarm Plot, an Alternative to Stripchart | 0.4.0 | 0.4.0 |
beezdemand Behavioral Economic Easy Demand | 0.1.0 | 0.1.0 |
bench High Precision Timing of R Expressions | 1.1.2 | 1.1.2 |
benchden 28 benchmark densities from Berlinet/Devroye (1994) | 1.0.5 | 1.0.5 |
BenfordTests Statistical Tests for Evaluating Conformity to Benford's Law | 1.2.0 | 1.2.0 |
bentcableAR Bent-Cable Regression for Independent Data or Autoregressive Time Series | 0.3.1 | 0.3.1 |
berryFunctions Function Collection Related to Plotting and Hydrology | 1.21.14 | 1.21.14 |
Bessel Computations and Approximations for Bessel Functions | 0.6-0 | 0.6-0 |
bestglm Best Subset GLM and Regression Utilities | 0.37.3 | 0.37.3 |
BetaBit Mini Games from Adventures of Beta and Bit | 2.1 | 2.1 |
betaboost Boosting Beta Regression | 1.0.1 | 1.0.1 |
betapart Partitioning Beta Diversity into Turnover and Nestedness Components | 1.6 | 1.6 |
betareg Beta Regression | 3.1-4 | 3.1-4 |
betategarch Simulation, Estimation and Forecasting of Beta-Skew-t-EGARCH Models | 3.3 | 3.3 |
BETS Brazilian Economic Time Series | 0.4.9 | 0.4.9 |
bezier Toolkit for Bezier Curves and Splines | 1.1.2 | 1.1.2 |
bfast Breaks for Additive Season and Trend | 1.6.1 | 1.6.1 |
BFpack Flexible Bayes Factor Testing of Scientific Expectations | 1.0.0 | 1.0.0 |
bfw Bayesian Framework for Computational Modeling | 0.4.2 | 0.4.2 |
BGGM Bayesian Gaussian Graphical Models | 2.0.4 | 2.0.4 |
bgmm Gaussian Mixture Modeling Algorithms and the Belief-Based Mixture Modeling | 1.8.5 | 1.8.5 |
BGPhazard Markov Beta and Gamma Processes for Modeling Hazard Rates | 2.1.0 | 2.1.0 |
BH Boost C++ Header Files | 1.81.0-1 | 1.81.0-1 |
BiasedUrn Biased Urn Model Distributions | 2.0.9 | 2.0.9 |
bibliometrix Comprehensive Science Mapping Analysis | 3.2.1 | 3.2.1 |
bibliometrixData Bibliometrix Example Datasets | 0.3.0 | 0.3.0 |
bibtex Bibtex Parser | 0.5.1 | 0.5.1 |
biclust BiCluster Algorithms | 2.0.3 | 2.0.3 |
biclustermd Biclustering with Missing Data | 0.2.3 | 0.2.3 |
bife Binary Choice Models with Fixed Effects | 0.7.2 | 0.7.2 |
BIFIEsurvey Tools for Survey Statistics in Educational Assessment | 3.4-15 | 3.4-15 |
bigassertr Assertion and Message Functions | 0.1.6 | 0.1.6 |
bigdatadist Distances for Machine Learning and Statistics in the Context of Big Data | 1.1 | 1.1 |
biglasso Extending Lasso Model Fitting to Big Data | 1.5.1 | 1.5.1 |
bigleaf Physical and Physiological Ecosystem Properties from Eddy Covariance Data | 0.8.2 | 0.8.2 |
biglm Bounded Memory Linear and Generalized Linear Models | 0.9-2.1 | 0.9-2.1 |
biglmm Bounded Memory Linear and Generalized Linear Models | 0.9-2 | 0.9-2 |
bigmemory Manage Massive Matrices with Shared Memory and Memory-Mapped Files | 4.6.1 | 4.6.1 |
bigmemory.sri A Shared Resource Interface for Bigmemory Project Packages | 0.1.6 | 0.1.6 |
bigparallelr Easy Parallel Tools | 0.3.2 | 0.3.2 |
bigrquery An Interface to Google's 'BigQuery' 'API' | 1.4.1 | 1.4.1 |
BigSEM Constructing Large Systems of Structural Equations | 0.2 | 0.2 |
bigsplines Smoothing Splines for Large Samples | 1.1-1 | 1.1-1 |
bigstatsr Statistical Tools for Filebacked Big Matrices | 1.5.6 | 1.5.6 |
bigtime Sparse Estimation of Large Time Series Models | 0.2.1 | 0.2.1 |
BigVAR Dimension Reduction Methods for Multivariate Time Series | 1.1.2 | 1.1.2 |
bimets Time Series and Econometric Modeling | 2.3.0 | 2.3.0 |
bindr Parametrized Active Bindings | 0.1.1 | 0.1.1 |
bindrcpp An 'Rcpp' Interface to Active Bindings | 0.2.2 | 0.2.2 |
binman A Binary Download Manager | 0.1.3 | 0.1.3 |
binom Binomial Confidence Intervals for Several Parameterizations | 1.1-1.1 | 1.1-1.1 |
binomSamSize Confidence Intervals and Sample Size Determination for a Binomial Proportion under Simple Random Sampling and Pooled Sampling | 0.1-5 | 0.1-5 |
binr Cut Numeric Values into Evenly Distributed Groups | 1.1.1 | 1.1.1 |
bio3d Biological Structure Analysis | 2.4-3 | 2.4-3 |
Biobase | 2.56.0 | 2.56.0 |
BiocFileCache | 2.4.0 | 2.4.0 |
BiocGenerics | 0.42.0 | 0.42.0 |
BiocIO | 1.6.0 | 1.6.0 |
BiocManager Access the Bioconductor Project Package Repository | 1.30.20 | 1.30.20 |
BiocNeighbors | 1.14.0 | 1.14.0 |
BiocParallel | 1.30.0 | 1.30.0 |
BiocSingular | 1.12.0 | 1.12.0 |
BiocStyle | 2.22.0 | 2.22.0 |
BiocVersion | 3.15.2 | 3.15.2 |
Biodem Biodemography Functions | 0.5 | 0.5 |
BiodiversityR Package for Community Ecology and Suitability Analysis | 2.15-1 | 2.15-1 |
bioinactivation Mathematical Modelling of (Dynamic) Microbial Inactivation | 1.2.3 | 1.2.3 |
BioMark Find Biomarkers in Two-Class Discrimination Problems | 0.4.5 | 0.4.5 |
biomaRt | 2.52.0 | 2.52.0 |
biomformat | 1.24.0 | 1.24.0 |
biomod2 Ensemble Platform for Species Distribution Modeling | 3.4.6 | 3.4.6 |
Biostrings | 2.64.0 | 2.64.0 |
biotic Calculation of Freshwater Biotic Indices | 0.1.2 | 0.1.2 |
bipartite Visualising Bipartite Networks and Calculating Some (Ecological) Indices | 2.18 | 2.18 |
birtr The R Package for "The Basics of Item Response Theory Using R" | 1.0.0 | 1.0.0 |
bit Classes and Methods for Fast Memory-Efficient Boolean Selections | 4.0.4 | 4.0.4 |
bit64 A S3 Class for Vectors of 64bit Integers | 4.0.5 | 4.0.5 |
bitops Bitwise Operations | 1.0-7 | 1.0-7 |
bivariate Bivariate Probability Distributions | 0.7.0 | 0.7.0 |
Bivariate.Pareto Bivariate Pareto Models | 1.0.3 | 1.0.3 |
BivarP Estimating the Parameters of Some Bivariate Distributions | 1.0 | 1.0 |
BivGeo Basu-Dhar Bivariate Geometric Distribution | 2.0.1 | 2.0.1 |
bivgeom Roy's Bivariate Geometric Distribution | 1.0 | 1.0 |
biwavelet Conduct Univariate and Bivariate Wavelet Analyses | 0.20.21 | 0.20.21 |
biwt Compute the Biweight Mean Vector and Covariance & Correlation Matrice | 1.0 | 1.0 |
bizdays Business Days Calculations and Utilities | 1.0.13 | 1.0.13 |
bjscrapeR An API Wrapper for the Bureau of Justice Statistics (BJS) | 0.1.0 | 0.1.0 |
blastula Easily Send HTML Email Messages | 0.3.3 | 0.3.3 |
blme Bayesian Linear Mixed-Effects Models | 1.0-5 | 1.0-5 |
BLModel Black-Litterman Posterior Distribution | 1.0.2 | 1.0.2 |
blob A Simple S3 Class for Representing Vectors of Binary Data ('BLOBS') | 1.2.4 | 1.2.4 |
blockmodeling Generalized and Classical Blockmodeling of Valued Networks | 1.0.5 | 1.0.5 |
blockmodels Latent and Stochastic Block Model Estimation by a 'V-EM' Algorithm | 1.1.5 | 1.1.5 |
blockrand Randomization for Block Random Clinical Trials | 1.5 | 1.5 |
blocksdesign Nested and Crossed Block Designs for Factorial and Unstructured Treatment Sets | 4.9 | 4.9 |
blotter | 0.16.0 | 0.16.0 |
BLR Bayesian Linear Regression | 1.6 | 1.6 |
bluster | 1.6.0 | 1.6.0 |
BMA Bayesian Model Averaging | 3.18.17 | 3.18.17 |
bmeta Bayesian Meta-Analysis and Meta-Regression | 0.1.2 | 0.1.2 |
Bmix Bayesian Sampling for Stick-Breaking Mixtures | 0.6 | 0.6 |
bmixture Bayesian Estimation for Finite Mixture of Distributions | 1.7 | 1.7 |
bmp Read Windows Bitmap (BMP) Images | 0.3 | 0.3 |
bmrm Bundle Methods for Regularized Risk Minimization Package | 4.1 | 4.1 |
BMS Bayesian Model Averaging Library | 0.3.5 | 0.3.5 |
BMT The BMT Distribution | 0.1.0.3 | 0.1.0.3 |
bnclassify Learning Discrete Bayesian Network Classifiers from Data | 0.4.7 | 0.4.7 |
bnlearn Bayesian Network Structure Learning, Parameter Learning and Inference | 4.8.1 | 4.8.1 |
bnnSurvival Bagged k-Nearest Neighbors Survival Prediction | 0.1.5 | 0.1.5 |
BNPTSclust A Bayesian Nonparametric Algorithm for Time Series Clustering | 2.0 | 2.0 |
BNSP Bayesian Non- And Semi-Parametric Model Fitting | 2.2.1 | 2.2.1 |
bnstruct Bayesian Network Structure Learning from Data with Missing Values | 1.0.14 | 1.0.14 |
boa Bayesian Output Analysis Program (BOA) for MCMC | 1.1.8-2 | 1.1.8-2 |
bodenmiller Profiling of Peripheral Blood Mononuclear Cells using CyTOF | 0.1.1 | 0.1.1 |
boilerpipeR Interface to the Boilerpipe Java Library | 1.3.2 | 1.3.2 |
BOIN Bayesian Optimal INterval (BOIN) Design for Single-Agent and Drug- Combination Phase I Clinical Trials | 2.7.2 | 2.7.2 |
bold Interface to Bold Systems API | 1.2.0 | 1.2.0 |
Bolstad Functions for Elementary Bayesian Inference | 0.2-41 | 0.2-41 |
Bolstad2 Bolstad Functions | 1.0-29 | 1.0-29 |
bomrang Australian Government Bureau of Meteorology ('BOM') Data Client | 0.7.4 | 0.7.4 |
bookdown Authoring Books and Technical Documents with R Markdown | 0.26 | 0.26 |
BoolNet Construction, Simulation and Analysis of Boolean Networks | 2.1.5 | 2.1.5 |
Boom Bayesian Object Oriented Modeling | 0.9.11 | 0.9.11 |
BoomSpikeSlab MCMC for Spike and Slab Regression | 1.2.5 | 1.2.5 |
boot Bootstrap Functions (Originally by Angelo Canty for S) | 1.3-28 | 1.3-28 |
boot.heterogeneity A Bootstrap-Based Heterogeneity Test for Meta-Analysis | 1.1.5 | 1.1.5 |
bootImpute Bootstrap Inference for Multiple Imputation | 1.2.0 | 1.2.0 |
bootnet Bootstrap Methods for Various Network Estimation Routines | 1.5 | 1.5 |
BootPR Bootstrap Prediction Intervals and Bias-Corrected Forecasting | 0.70 | 0.70 |
bootstrap Functions for the Book "An Introduction to the Bootstrap" | 2019.6 | 2019.6 |
Boruta Wrapper Algorithm for All Relevant Feature Selection | 8.0.0 | 8.0.0 |
BoSSA A Bunch of Structure and Sequence Analysis | 3.7 | 3.7 |
boussinesq Analytic Solutions for (Ground-Water) Boussinesq Equation | 1.0.4 | 1.0.4 |
boxr Interface for the 'Box.com API' | 0.3.6 | 0.3.6 |
bpca Biplot of Multivariate Data Based on Principal Components Analysis | 1.3-4 | 1.3-4 |
bpcp Beta Product Confidence Procedure for Right Censored Data | 1.4.2 | 1.4.2 |
bqtl Bayesian QTL Mapping Toolkit | 1.0-34 | 1.0-34 |
BradleyTerry2 Bradley-Terry Models | 1.1-2 | 1.1-2 |
brainR Helper Functions to 'misc3d' and 'rgl' Packages for Brain Imaging | 1.6.0 | 1.6.0 |
brainwaver Basic wavelet analysis of multivariate time series with a<U+000a>visualisation and parametrisation using graph theory. | 1.6 | 1.6 |
brandwatchR 'Brandwatch' API to R | 0.3.0 | 0.3.0 |
breakDown Model Agnostic Explainers for Individual Predictions | 0.2.1 | 0.2.1 |
bReeze Functions for Wind Resource Assessment | 0.4-3 | 0.4-3 |
brew Templating Framework for Report Generation | 1.0-8 | 1.0-8 |
brglm Bias Reduction in Binomial-Response Generalized Linear Models | 0.7.2 | 0.7.2 |
brglm2 Bias Reduction in Generalized Linear Models | 0.9 | 0.9 |
bridgedist An Implementation of the Bridge Distribution with Logit-Link as in Wang and Louis (2003) | 0.1.1 | 0.1.1 |
bridgesampling Bridge Sampling for Marginal Likelihoods and Bayes Factors | 1.1-2 | 1.1-2 |
brio Basic R Input Output | 1.1.3 | 1.1.3 |
brlrmr Bias Reduction with Missing Binary Response | 0.1.7 | 0.1.7 |
Brobdingnag Very Large Numbers in R | 1.2-9 | 1.2-9 |
broman Karl Broman's R Code | 0.80 | 0.80 |
broom Convert Statistical Objects into Tidy Tibbles | 1.0.4 | 1.0.4 |
broom.helpers Helpers for Model Coefficients Tibbles | 1.7.0 | 1.7.0 |
broom.mixed Tidying Methods for Mixed Models | 0.2.9.4 | 0.2.9.4 |
brotli A Compression Format Optimized for the Web | 1.3.0 | 1.3.0 |
brranching Fetch 'Phylogenies' from Many Sources | 0.7.0 | 0.7.0 |
bsam Bayesian State-Space Models for Animal Movement | 1.1.3 | 1.1.3 |
bsamGP Bayesian Spectral Analysis Models using Gaussian Process Priors | 1.2.4 | 1.2.4 |
BSDA Basic Statistics and Data Analysis | 1.2.1 | 1.2.1 |
BSgenome | 1.64.0 | 1.64.0 |
bshazard Nonparametric Smoothing of the Hazard Function | 1.1 | 1.1 |
bslib Custom 'Bootstrap' 'Sass' Themes for 'shiny' and 'rmarkdown' | 0.4.1 | 0.4.1 |
bspec Bayesian Spectral Inference | 1.6 | 1.6 |
bspmma Bayesian Semiparametric Models for Meta-Analysis | 0.1-2 | 0.1-2 |
bssm Bayesian Inference of Non-Linear and Non-Gaussian State Space Models | 2.0.1 | 2.0.1 |
bst Gradient Boosting | 0.3-24 | 0.3-24 |
bsts Bayesian Structural Time Series | 0.9.9 | 0.9.9 |
BTLLasso Modelling Heterogeneity in Paired Comparison Data | 0.1-11 | 0.1-11 |
BTM Biterm Topic Models for Short Text | 0.3.7 | 0.3.7 |
bundesbank Download Data from Bundesbank | 0.1-9 | 0.1-9 |
BurStFin Burns Statistics Financial | 1.3 | 1.3 |
BurStMisc Burns Statistics Miscellaneous | 1.1 | 1.1 |
BVAR Hierarchical Bayesian Vector Autoregression | 1.0.4 | 1.0.4 |
bvartools Bayesian Inference of Vector Autoregressive and Error Correction Models | 0.2.1 | 0.2.1 |
bvls The Stark-Parker algorithm for bounded-variable least squares | 1.4 | 1.4 |
BVS Bayesian Variant Selection: Bayesian Model Uncertainty<U+000a>Techniques for Genetic Association Studies | 4.12.1 | 4.12.1 |
BWStest Baumgartner Weiss Schindler Test of Equal Distributions | 0.2.2 | 0.2.2 |
C50 C5.0 Decision Trees and Rule-Based Models | 0.1.8 | 0.1.8 |
ca Simple, Multiple and Joint Correspondence Analysis | 0.71.1 | 0.71.1 |
cabinets Project Specific Workspace Organization Templates | 0.6.0 | 0.6.0 |
cabootcrs Bootstrap Confidence Regions for Simple and Multiple Correspondence Analysis | 2.1.0 | 2.1.0 |
cachem Cache R Objects with Automatic Pruning | 1.0.7 | 1.0.7 |
cacIRT Classification Accuracy and Consistency under Item Response Theory | 1.4 | 1.4 |
CADFtest A Package to Perform Covariate Augmented Dickey-Fuller Unit Root Tests | 0.3-3 | 0.3-3 |
caffsim Simulation of Plasma Caffeine Concentrations by Using Population Pharmacokinetic Model | 0.2.2 | 0.2.2 |
cAIC4 Conditional Akaike Information Criterion for 'lme4' and 'nlme' | 1.0 | 1.0 |
Cairo R Graphics Device using Cairo Graphics Library for Creating High-Quality Bitmap (PNG, JPEG, TIFF), Vector (PDF, SVG, PostScript) and Display (X11 and Win32) Output | 1.5-15 | 1.5-15 |
cairoDevice Embeddable Cairo Graphics Device Driver | 2.28.2.1 | 2.28.2.1 |
calculus High Dimensional Numerical and Symbolic Calculus | 1.0.1 | 1.0.1 |
calibrate Calibration of Scatterplot and Biplot Axes | 1.7.7 | 1.7.7 |
CalibrateSSB Weighting and Estimation for Panel Data with Non-Response | 1.3.0 | 1.3.0 |
calibrator Bayesian Calibration of Complex Computer Codes | 1.2-8 | 1.2-8 |
callr Call R from R | 3.7.3 | 3.7.3 |
CAMAN Finite Mixture Models and Meta-Analysis Tools - Based on C.A.MAN | 0.76 | 0.76 |
cancensus Access, Retrieve, and Work with Canadian Census Data and Geography | 0.5.0 | 0.5.0 |
candisc Visualizing Generalized Canonical Discriminant and Canonical Correlation Analysis | 0.8-6 | 0.8-6 |
caper Comparative Analyses of Phylogenetics and Evolution in R | 1.0.1 | 1.0.1 |
captr Client for the Captricity API | 0.3.0 | 0.3.0 |
car Companion to Applied Regression | 3.1-1 | 3.1-1 |
caRamel Automatic Calibration by Evolutionary Multi Objective Algorithm | 1.3 | 1.3 |
CARBayes Spatial Generalised Linear Mixed Models for Areal Unit Data | 5.3 | 5.3 |
CARBayesdata Data Used in the Vignettes Accompanying the CARBayes and CARBayesST Packages | 3.0 | 3.0 |
CARBayesST Spatio-Temporal Generalised Linear Mixed Models for Areal Unit Data | 3.3.1 | 3.3.1 |
carData Companion to Applied Regression Data Sets | 3.0-5 | 3.0-5 |
caret Classification and Regression Training | 6.0-92 | 6.0-92 |
caribou Estimation of Caribou Abundance Based on Radio Telemetry Data | 1.1-1 | 1.1-1 |
cartogram Create Cartograms with R | 0.2.2 | 0.2.2 |
cartography Thematic Cartography | 3.0.1 | 3.0.1 |
carx Censored Autoregressive Model with Exogenous Covariates | 0.7.1 | 0.7.1 |
casebase Fitting Flexible Smooth-in-Time Hazards and Risk Functions via Logistic and Multinomial Regression | 0.10.3 | 0.10.3 |
cassandRa Finds Missing Links and Metric Confidence Intervals in Ecological Bipartite Networks | 0.1.0 | 0.1.0 |
castor Efficient Phylogenetics on Large Trees | 1.7.8 | 1.7.8 |
cat Analysis and Imputation of Categorical-Variable Datasets with Missing Values | 0.0-7 | 0.0-7 |
catmap Case-Control and TDT Meta-Analysis Package | 1.6.4 | 1.6.4 |
caTools Tools: Moving Window Statistics, GIF, Base64, ROC AUC, etc | 1.18.2 | 1.18.2 |
catR Generation of IRT Response Patterns under Computerized Adaptive Testing | 3.17 | 3.17 |
catspec Special models for categorical variables | 0.97 | 0.97 |
CAvariants Correspondence Analysis Variants | 5.8 | 5.8 |
cba Clustering for Business Analytics | 0.2-23 | 0.2-23 |
cbinom Continuous Analog of a Binomial Distribution | 1.6 | 1.6 |
cbsodataR Statistics Netherlands (CBS) Open Data API Client | 0.5.1 | 0.5.1 |
cccp Cone Constrained Convex Problems | 0.2-9 | 0.2-9 |
ccdrAlgorithm CCDr Algorithm for Learning Sparse Gaussian Bayesian Networks | 0.0.6 | 0.0.6 |
cclust Convex Clustering Methods and Clustering Indexes | 0.6-25 | 0.6-25 |
CDM Cognitive Diagnosis Modeling | 8.2-6 | 8.2-6 |
CDNmoney Components of Canadian Monetary and Credit Aggregates | 2012.4-2 | 2012.4-2 |
cdparcoord Top Frequency-Based Parallel Coordinates | 1.0.1 | 1.0.1 |
cds Constrained Dual Scaling for Detecting Response Styles | 1.0.3 | 1.0.3 |
CDVine Statistical Inference of C- And D-Vine Copulas | 1.4 | 1.4 |
CEC Cross-Entropy Clustering | 0.10.3 | 0.10.3 |
cec2013 Benchmark functions for the Special Session and Competition on Real-Parameter Single Objective Optimization at CEC-2013 | 0.1-5 | 0.1-5 |
celestial Collection of Common Astronomical Conversion Routines and Functions | 1.4.6 | 1.4.6 |
cellranger Translate Spreadsheet Cell Ranges to Rows and Columns | 1.1.0 | 1.1.0 |
cellWise Analyzing Data with Cellwise Outliers | 2.4.0 | 2.4.0 |
censReg Censored Regression (Tobit) Models | 0.5-34 | 0.5-34 |
censusapi Retrieve Data from the Census APIs | 0.8.0 | 0.8.0 |
censusGeography Changes United States Census Geographic Code into Name of Location | 0.1.0 | 0.1.0 |
cents Censored time series | 0.1-41 | 0.1-41 |
CEoptim Cross-Entropy R Package for Optimization | 1.2 | 1.2 |
ceterisParibus Ceteris Paribus Profiles | 0.4.2 | 0.4.2 |
CFC Cause-Specific Framework for Competing-Risk Analysis | 1.2.0 | 1.2.0 |
ChainLadder Statistical Methods and Models for Claims Reserving in General Insurance | 0.2.17 | 0.2.17 |
chandwich Chandler-Bate Sandwich Loglikelihood Adjustment | 1.1.5 | 1.1.5 |
changepoint Methods for Changepoint Detection | 2.2.3 | 2.2.3 |
changepoint.mv Changepoint Analysis for Multivariate Time Series | 1.0.2 | 1.0.2 |
changepoint.np Methods for Nonparametric Changepoint Detection | 1.0.5 | 1.0.5 |
chebpol Multivariate Interpolation | 2.1-2 | 2.1-2 |
checkmate Fast and Versatile Argument Checks | 2.1.0 | 2.1.0 |
checkpoint Install Packages from Snapshots on the Checkpoint Server for Reproducibility | 1.0.2 | 1.0.2 |
checkr Check the Properties of Common R Objects | 0.5.0 | 0.5.0 |
chemCal Calibration Functions for Analytical Chemistry | 0.2.3 | 0.2.3 |
ChemoSpec2D Exploratory Chemometrics for 2D Spectroscopy | 0.5.0 | 0.5.0 |
ChemoSpecUtils Functions Supporting Packages ChemoSpec and ChemoSpec2D | 1.0.0 | 1.0.0 |
cherryblossom Cherry Blossom Run Race Results | 0.1.0 | 0.1.0 |
chk Check User-Supplied Function Arguments | 0.8.1 | 0.8.1 |
CHNOSZ Thermodynamic Calculations and Diagrams for Geochemistry | 2.0.0 | 2.0.0 |
choroplethr Simplify the Creation of Choropleth Maps in R | 3.7.0 | 3.7.0 |
choroplethrAdmin1 Contains an Administrative-Level-1 Map of the World | 1.1.1 | 1.1.1 |
choroplethrMaps Contains Maps Used by the 'choroplethr' Package | 1.0.1 | 1.0.1 |
chron Chronological Objects which Can Handle Dates and Times | 2.3-59 | 2.3-59 |
CHsharp Choi and Hall Style Data Sharpening | 0.4 | 0.4 |
CIAAWconsensus Isotope Ratio Meta-Analysis | 1.3 | 1.3 |
circlize Circular Visualization | 0.4.15 | 0.4.15 |
CircSpaceTime Spatial and Spatio-Temporal Bayesian Model for Circular Data | 0.9.0 | 0.9.0 |
CircStats Circular Statistics, from "Topics in Circular Statistics" (2001) | 0.2-6 | 0.2-6 |
circular Circular Statistics | 0.4-95 | 0.4-95 |
circumplex Analysis and Visualization of Circular Data | 0.3.8 | 0.3.8 |
CityWaterBalance Track Flows of Water Through an Urban System | 0.1.0 | 0.1.0 |
Ckmeans.1d.dp Optimal, Fast, and Reproducible Univariate Clustering | 4.3.4 | 4.3.4 |
Claddis Measuring Morphological Diversity and Evolutionary Tempo | 0.6.3 | 0.6.3 |
clarifai Access to Clarifai API | 0.4.2 | 0.4.2 |
class Functions for Classification | 7.3-21 | 7.3-21 |
classInt Choose Univariate Class Intervals | 0.4-9 | 0.4-9 |
cleangeo Cleaning Geometries from Spatial Objects | 0.2-4 | 0.2-4 |
cli Helpers for Developing Command Line Interfaces | 3.6.1 | 3.6.1 |
cliapp Create Rich Command Line Applications | 0.1.1 | 0.1.1 |
clifro Easily Download and Visualise Climate Data from CliFlo | 3.2-5 | 3.2-5 |
climate Interface to Download Meteorological (and Hydrological) Datasets | 1.0.5 | 1.0.5 |
climatol Climate Tools (Series Homogenization and Derived Products) | 3.1.2 | 3.1.2 |
climdex.pcic PCIC Implementation of Climdex Routines | 1.1-11 | 1.1-11 |
clinfun Clinical Trial Design and Data Analysis Functions | 1.1.1 | 1.1.1 |
clinPK Clinical Pharmacokinetics Toolkit | 0.11.1 | 0.11.1 |
clinsig Clinical Significance Functions | 1.2 | 1.2 |
clipr Read and Write from the System Clipboard | 0.8.0 | 0.8.0 |
clisymbols Unicode Symbols at the R Prompt | 1.2.0 | 1.2.0 |
clock Date-Time Types and Tools | 0.6.0 | 0.6.0 |
cloudml Interface to the Google Cloud Machine Learning Platform | 0.6.1 | 0.6.1 |
clpAPI R Interface to C API of COIN-or Clp | 1.3.1 | 1.3.1 |
CLSOCP A smoothing Newton method SOCP solver | 1.0 | 1.0 |
clubSandwich Cluster-Robust (Sandwich) Variance Estimators with Small-Sample Corrections | 0.5.8 | 0.5.8 |
clue Cluster Ensembles | 0.3-64 | 0.3-64 |
cluster "Finding Groups in Data": Cluster Analysis Extended Rousseeuw et al. | 2.1.3 | 2.1.3 |
clusterCrit Clustering Indices | 1.2.8 | 1.2.8 |
clusterfly Explore clustering interactively using R and GGobi | 0.4 | 0.4 |
clusterGeneration Random Cluster Generation (with Specified Degree of Separation) | 1.3.7 | 1.3.7 |
clustermq Evaluate Function Calls on HPC Schedulers (LSF, SGE, SLURM, PBS/Torque) | 0.8.95.5 | 0.8.95.5 |
clusterPower Power Calculations for Cluster-Randomized and Cluster-Randomized Crossover Trials | 0.7.0 | 0.7.0 |
ClusterR Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans, K-Medoids and Affinity Propagation Clustering | 1.3.0 | 1.3.0 |
clusterRepro Reproducibility of Gene Expression Clusters | 0.9 | 0.9 |
clusterSEs Calculate Cluster-Robust p-Values and Confidence Intervals | 2.6.5 | 2.6.5 |
clusterSim Searching for Optimal Clustering Procedure for a Data Set | 0.50-1 | 0.50-1 |
ClustImpute K-Means Clustering with Build-in Missing Data Imputation | 0.2.4 | 0.2.4 |
clustMixType k-Prototypes Clustering for Mixed Variable-Type Data | 0.3-9 | 0.3-9 |
ClustVarLV Clustering of Variables Around Latent Variables | 2.1.1 | 2.1.1 |
clustvarsel Variable Selection for Gaussian Model-Based Clustering | 2.3.4 | 2.3.4 |
clv Cluster Validation Techniques | 0.3-2.2 | 0.3-2.2 |
clValid Validation of Clustering Results | 0.7 | 0.7 |
cmaes Covariance Matrix Adapting Evolutionary Strategy | 1.0-12 | 1.0-12 |
cmaesr Covariance Matrix Adaptation Evolution Strategy | 1.0.3 | 1.0.3 |
CMC Cronbach-Mesbah Curve | 1.0 | 1.0 |
CMLS Constrained Multivariate Least Squares | 1.0-0 | 1.0-0 |
cmm Categorical Marginal Models | 0.12 | 0.12 |
cmocean Beautiful Colour Maps for Oceanography | 0.3-1 | 0.3-1 |
cmprsk Subdistribution Analysis of Competing Risks | 2.2-11 | 2.2-11 |
cmprskQR Analysis of Competing Risks Using Quantile Regressions | 0.9.2 | 0.9.2 |
cmrutils Misc Functions of the Center for Mathematical Research | 1.3.1 | 1.3.1 |
cmvnorm The Complex Multivariate Gaussian Distribution | 1.0-7 | 1.0-7 |
cncaGUI Canonical Non-Symmetrical Correspondence Analysis in R | 1.1 | 1.1 |
cNORM Continuous Norming | 3.0.2 | 3.0.2 |
coalescentMCMC MCMC Algorithms for the Coalescent | 0.4-4 | 0.4-4 |
coarseDataTools Analysis of Coarsely Observed Data | 0.6-6 | 0.6-6 |
cobalt Covariate Balance Tables and Plots | 4.4.1 | 4.4.1 |
cobs Constrained B-Splines (Sparse Matrix Based) | 1.3-5 | 1.3-5 |
CoClust Copula Based Cluster Analysis | 0.3-2 | 0.3-2 |
COCONUT COmbat CO-Normalization Using conTrols (COCONUT) | 1.0.2 | 1.0.2 |
cocor Comparing Correlations | 1.1-4 | 1.1-4 |
cocorresp Co-Correspondence Analysis Methods | 0.4-3 | 0.4-3 |
cocron Statistical Comparisons of Two or more Alpha Coefficients | 1.0-1 | 1.0-1 |
coda Output Analysis and Diagnostics for MCMC | 0.19-4 | 0.19-4 |
codalm Transformation-Free Linear Regression for Compositional Outcomes and Predictors | 0.1.2 | 0.1.2 |
cOde Automated C Code Generation for 'deSolve', 'bvpSolve' | 1.1.1 | 1.1.1 |
codetools Code Analysis Tools for R | 0.2-19 | 0.2-19 |
coefplot Plots Coefficients from Fitted Models | 1.2.8 | 1.2.8 |
coga Convolution of Gamma Distributions | 1.1.1 | 1.1.1 |
CoImp Copula Based Imputation Method | 1.0 | 1.0 |
coin Conditional Inference Procedures in a Permutation Test Framework | 1.4-2 | 1.4-2 |
cointReg Parameter Estimation and Inference in a Cointegrating Regression | 0.2.0 | 0.2.0 |
colf Constrained Optimization on Linear Function | 0.1.3 | 0.1.3 |
collapse Advanced and Fast Data Transformation | 1.9.3 | 1.9.3 |
collections High Performance Container Data Types | 0.3.5 | 0.3.5 |
CollocInfer Collocation Inference for Dynamic Systems | 1.0.4 | 1.0.4 |
colorRamps Builds Color Tables | 2.3.1 | 2.3.1 |
colorspace A Toolbox for Manipulating and Assessing Colors and Palettes | 2.1-0 | 2.1-0 |
colourpicker A Colour Picker Tool for Shiny and for Selecting Colours in Plots | 1.2.0 | 1.2.0 |
colourvalues Assigns Colours to Values | 0.3.8 | 0.3.8 |
combinat combinatorics utilities | 0.0-8 | 0.0-8 |
CombMSC Combined Model Selection Criteria | 1.4.2.1 | 1.4.2.1 |
commonmark High Performance CommonMark and Github Markdown Rendering in R | 1.8.0 | 1.8.0 |
CommonTrend Extract and plot common trends from a cointegration system.<U+000a>Calculate P-value for Johansen Statistics. | 0.7-1 | 0.7-1 |
compareC Compare Two Correlated C Indices with Right-Censored Survival Outcome | 1.3.2 | 1.3.2 |
compareGroups Descriptive Analysis by Groups | 4.5.1 | 4.5.1 |
competitiontoolbox A Graphical User Interface for Antitrust and Trade Practitioners | 0.7.0 | 0.7.0 |
compHclust Complementary Hierarchical Clustering | 1.0-3 | 1.0-3 |
compiler | 4.2.3 | 4.2.3 |
ComplexUpset Create Complex UpSet Plots Using 'ggplot2' Components | 1.3.3 | 1.3.3 |
complmrob Robust Linear Regression with Compositional Data as Covariates | 0.7.0 | 0.7.0 |
CompLognormal Functions for actuarial scientists | 3.0 | 3.0 |
Compositional Compositional Data Analysis | 6.2 | 6.2 |
compositions Compositional Data Analysis | 2.0-5 | 2.0-5 |
compound.Cox Univariate Feature Selection and Compound Covariate for Predicting Survival | 3.27 | 3.27 |
Compounding Computing Continuous Distributions | 1.0.2 | 1.0.2 |
CompQuadForm Distribution Function of Quadratic Forms in Normal Variables | 1.4.3 | 1.4.3 |
CompRandFld Composite-Likelihood Based Analysis of Random Fields | 1.0.3-6 | 1.0.3-6 |
compute.es Compute Effect Sizes | 0.2-5 | 0.2-5 |
concor Concordance | 1.0-0.1 | 1.0-0.1 |
concreg Concordance Regression | 0.7 | 0.7 |
condGEE Parameter Estimation in Conditional GEE for Recurrent Event Gap Times | 0.2.0 | 0.2.0 |
conditionz Control How Many Times Conditions are Thrown | 0.1.0 | 0.1.0 |
condMVNorm Conditional Multivariate Normal Distribution | 2020.1 | 2020.1 |
condSURV Estimation of the Conditional Survival Function for Ordered Multivariate Failure Time Data | 2.0.4 | 2.0.4 |
coneproj Primal or Dual Cone Projections with Routines for Constrained Regression | 1.16 | 1.16 |
conf.design Construction of factorial designs | 2.0.0 | 2.0.0 |
config Manage Environment Specific Configuration Values | 0.3.1 | 0.3.1 |
conflicted An Alternative Conflict Resolution Strategy | 1.1.0 | 1.1.0 |
ConfoundedMeta Sensitivity Analyses for Unmeasured Confounding in Meta-Analyses | 1.3.0 | 1.3.0 |
conicfit Algorithms for Fitting Circles, Ellipses and Conics Based on the Work by Prof. Nikolai Chernov | 1.0.4 | 1.0.4 |
conjoint An Implementation of Conjoint Analysis Method | 1.41 | 1.41 |
conquestr An R Package to Extend 'ACER ConQuest' | 1.0.7 | 1.0.7 |
constants Reference on Constants, Units and Uncertainty | 1.0.1 | 1.0.1 |
constrainedKriging Constrained, Covariance-Matching Constrained and Universal Point or Block Kriging | 0.2.4 | 0.2.4 |
container Extending Base 'R' Lists | 1.0.2 | 1.0.2 |
contfrac Continued Fractions | 1.1-12 | 1.1-12 |
controlTest Quantile Comparison for Two-Sample Right-Censored Survival Data | 1.1.0 | 1.1.0 |
convevol Analysis of Convergent Evolution | 2.0.0 | 2.0.0 |
convey Income Concentration Analysis with Complex Survey Samples | 0.2.5 | 0.2.5 |
coop Co-Operation: Fast Covariance, Correlation, and Cosine Similarity Operations | 0.6-3 | 0.6-3 |
copBasic General Bivariate Copula Theory and Many Utility Functions | 2.1.9 | 2.1.9 |
copula Multivariate Dependence with Copulas | 1.1-2 | 1.1-2 |
copulaData Data Sets for Copula Modeling | 0.0-1 | 0.0-1 |
copulaedas Estimation of Distribution Algorithms Based on Copulas | 1.4.3 | 1.4.3 |
CopulaREMADA Copula Mixed Models for Multivariate Meta-Analysis of Diagnostic Test Accuracy Studies | 1.5 | 1.5 |
CopyDetect Computing Response Similarity Indices for Multiple-Choice Tests | 1.3 | 1.3 |
CORElearn Classification, Regression and Feature Evaluation | 1.57.3 | 1.57.3 |
corHMM Hidden Markov Models of Character Evolution | 2.7 | 2.7 |
coronavirus The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Dataset | 0.4.0 | 0.4.0 |
corpcor Efficient Estimation of Covariance and (Partial) Correlation | 1.6.10 | 1.6.10 |
corpora Statistics and Data Sets for Corpus Frequency Data | 0.5-1 | 0.5-1 |
corporaexplorer A 'Shiny' App for Exploration of Text Collections | 0.8.5 | 0.8.5 |
corrplot Visualization of a Correlation Matrix | 0.92 | 0.92 |
cosinor Tools for Estimating and Predicting the Cosinor Model | 1.2.2 | 1.2.2 |
cosinor2 Extended Tools for Cosinor Analysis of Rhythms | 0.2.1 | 0.2.1 |
cosmoFns Functions for Cosmological Distances, Times, Luminosities, Etc | 1.1-1 | 1.1-1 |
costat Time Series Costationarity Determination | 2.4 | 2.4 |
countrycode Convert Country Names and Country Codes | 1.4.0 | 1.4.0 |
countytimezones Convert from UTC to Local Time for United States Counties | 1.0.0 | 1.0.0 |
countyweather Compiles Meterological Data for U.S. Counties | 0.1.0 | 0.1.0 |
covLCA Latent Class Models with Covariate Effects on Underlying and<U+000a>Measured Variables | 1.0 | 1.0 |
covr Test Coverage for Packages | 3.5.1 | 3.5.1 |
covRobust Robust Covariance Estimation via Nearest Neighbor Cleaning | 1.1-3 | 1.1-3 |
covsep Tests for Determining if the Covariance Structure of 2-Dimensional Data is Separable | 1.1.0 | 1.1.0 |
cowplot Streamlined Plot Theme and Plot Annotations for 'ggplot2' | 1.1.1 | 1.1.1 |
cowsay Messages, Warnings, Strings with Ascii Animals | 0.8.0 | 0.8.0 |
CoxBoost Cox models by likelihood based boosting for a single survival<U+000a>endpoint or competing risks | 1.4 | 1.4 |
coxed Duration-Based Quantities of Interest for the Cox Proportional Hazards Model | 0.3.3 | 0.3.3 |
coxinterval Cox-Type Models for Interval-Censored Data | 1.2 | 1.2 |
coxme Mixed Effects Cox Models | 2.2-18.1 | 2.2-18.1 |
coxphf Cox Regression with Firth's Penalized Likelihood | 1.13.1 | 1.13.1 |
coxphw Weighted Estimation in Cox Regression | 4.0.2 | 4.0.2 |
CoxRidge Cox Models with Dynamic Ridge Penalties | 0.9.2 | 0.9.2 |
coxrobust Fit Robustly Proportional Hazards Regression Model | 1.0.1 | 1.0.1 |
coxsei Fitting a CoxSEI Model | 0.3 | 0.3 |
CPBayes Bayesian Meta Analysis for Studying Cross-Phenotype Genetic Associations | 1.1.0 | 1.1.0 |
cpd Complex Pearson Distributions | 0.1.0 | 0.1.0 |
CPE Concordance Probability Estimates in Survival Analysis | 1.5.2 | 1.5.2 |
cpk Clinical Pharmacokinetics | 1.3-1 | 1.3-1 |
cplm Compound Poisson Linear Models | 0.7-10 | 0.7-10 |
cpp11 A C++11 Interface for R's C Interface | 0.4.3 | 0.4.3 |
Cprob The Conditional Probability Function of a Competing Event | 1.4.1 | 1.4.1 |
CR Power Calculation for Weighted Log-Rank Tests in Cure Rate<U+000a>Models | 1.0 | 1.0 |
cramer Multivariate Nonparametric Cramer-Test for the Two-Sample-Problem | 0.9-3 | 0.9-3 |
crawl Fit Continuous-Time Correlated Random Walk Models to Animal Movement Data | 2.2.1 | 2.2.1 |
crayon Colored Terminal Output | 1.5.2 | 1.5.2 |
crch Censored Regression with Conditional Heteroscedasticity | 1.1-1 | 1.1-1 |
credentials Tools for Managing SSH and Git Credentials | 1.3.2 | 1.3.2 |
CreditMetrics Functions for calculating the CreditMetrics risk model | 0.0-2 | 0.0-2 |
credule Credit Default Swap Functions | 0.1.4 | 0.1.4 |
crfsuite Conditional Random Fields for Labelling Sequential Data in Natural Language Processing | 0.4.1 | 0.4.1 |
CRM Continual Reassessment Method (CRM) for Phase I Clinical Trials | 1.2.4 | 1.2.4 |
crminer Fetch 'Scholary' Full Text from 'Crossref' | 0.4.0 | 0.4.0 |
crossdes Construction of Crossover Designs | 1.1-2 | 1.1-2 |
crosstalk Inter-Widget Interactivity for HTML Widgets | 1.2.0 | 1.2.0 |
crrp Penalized Variable Selection in Competing Risks Regression | 1.0 | 1.0 |
crrSC Competing Risks Regression for Stratified and Clustered Data | 1.1.2 | 1.1.2 |
crrstep Stepwise Covariate Selection for the Fine & Gray Competing Risks Regression Model | 2015-2.1 | 2015-2.1 |
crs Categorical Regression Splines | 0.15-37 | 0.15-37 |
crseEventStudy A Robust and Powerful Test of Abnormal Stock Returns in Long-Horizon Event Studies | 1.2.2 | 1.2.2 |
crskdiag Diagnostics for Fine and Gray Model | 1.0.1 | 1.0.1 |
crsmeta Extract Coordinate System Metadata | 0.3.0 | 0.3.0 |
CRTgeeDR Doubly Robust Inverse Probability Weighted Augmented GEE Estimator | 2.0.1 | 2.0.1 |
CRTSize Sample Size Estimation Functions for Cluster Randomized Trials | 1.2 | 1.2 |
crul HTTP Client | 1.3 | 1.3 |
crunch Crunch.io Data Tools | 1.30.1 | 1.30.1 |
crunchy Shiny Apps on Crunch | 0.3.3 | 0.3.3 |
cshapes The CShapes 2.0 Dataset and Utilities | 2.0 | 2.0 |
csn Closed Skew-Normal Distribution | 1.1.3 | 1.1.3 |
cstab Selection of Number of Clusters via Normalized Clustering Instability | 0.2-2 | 0.2-2 |
ctmcmove Modeling Animal Movement with Continuous-Time Discrete-Space Markov Chains | 1.2.9 | 1.2.9 |
ctmm Continuous-Time Movement Modeling | 0.6.1 | 0.6.1 |
ctsem Continuous Time Structural Equation Modelling | 3.6.0 | 3.6.0 |
CTT Classical Test Theory Functions | 2.3.3 | 2.3.3 |
CTTShiny Classical Test Theory via Shiny | 0.1 | 0.1 |
cubature Adaptive Multivariate Integration over Hypercubes | 2.0.4.6 | 2.0.4.6 |
cubelyr A Data Cube 'dplyr' Backend | 1.0.2 | 1.0.2 |
cubfits Codon Usage Bias Fits | 0.1-4 | 0.1-4 |
Cubist Rule- And Instance-Based Regression Modeling | 0.4.2.1 | 0.4.2.1 |
curl A Modern and Flexible Web Client for R | 5.0.0 | 5.0.0 |
currentSurvival Estimation of CCI and CLFS Functions | 1.1 | 1.1 |
cutoffR CUTOFF: A Spatio-temporal Imputation Method | 1.0 | 1.0 |
cvar Compute Expected Shortfall and Value at Risk for Continuous Distributions | 0.5 | 0.5 |
cvAUC Cross-Validated Area Under the ROC Curve Confidence Intervals | 1.1.4 | 1.1.4 |
CVST Fast Cross-Validation via Sequential Testing | 0.2-3 | 0.2-3 |
CVThresh Level-Dependent Cross-Validation Thresholding | 1.1.2 | 1.1.2 |
cvTools Cross-validation tools for regression models | 0.3.2 | 0.3.2 |
CVXR Disciplined Convex Optimization | 1.0-11 | 1.0-11 |
cwhmisc Miscellaneous Functions for Math, Plotting, Printing, Statistics, Strings, and Tools | 6.6 | 6.6 |
cyclestreets Cycle Routing and Data for Cycling Advocacy | 0.5.3 | 0.5.3 |
cyclocomp Cyclomatic Complexity of R Code | 1.1.0 | 1.1.0 |
cymruservices Query 'Team Cymru' 'IP' Address, Autonomous System Number ('ASN'), Border Gateway Protocol ('BGP'), Bogon and 'Malware' Hash Data Services | 0.5.0 | 0.5.0 |
cytofan Plot Fan Plots for Cytometry Data using 'ggplot2' | 0.1.0 | 0.1.0 |
daarem Damped Anderson Acceleration with Epsilon Monotonicity for Accelerating EM-Like Monotone Algorithms | 0.7 | 0.7 |
daewr Design and Analysis of Experiments with R | 1.2-7 | 1.2-7 |
dagitty Graphical Analysis of Structural Causal Models | 0.3-1 | 0.3-1 |
DAISIE Dynamical Assembly of Islands by Speciation, Immigration and Extinction | 3.0.1 | 3.0.1 |
DAKS Data Analysis and Knowledge Spaces | 2.1-3 | 2.1-3 |
DALEX moDel Agnostic Language for Exploration and eXplanation | 2.4.3 | 2.4.3 |
dalmatian Automating the Fitting of Double Linear Mixed Models in 'JAGS' and 'nimble' | 1.0.0 | 1.0.0 |
DAMOCLES Dynamic Assembly Model of Colonization, Local Extinction and Speciation | 2.3 | 2.3 |
data.table Extension of `data.frame` | 1.14.8 | 1.14.8 |
data.tree General Purpose Hierarchical Data Structure | 1.0.0 | 1.0.0 |
DatabionicSwarm Swarm Intelligence for Self-Organized Clustering | 1.1.6 | 1.1.6 |
datamart Unified access to your data sources | 0.5.2 | 0.5.2 |
dataone R Interface to the DataONE REST API | 2.2.2 | 2.2.2 |
datapack A Flexible Container to Transport and Manipulate Data and Associated Resources | 1.4.1 | 1.4.1 |
dataRetrieval Retrieval Functions for USGS and EPA Hydrology and Water Quality Data | 2.7.12 | 2.7.12 |
datarobot 'DataRobot' Predictive Modeling API | 2.18.2 | 2.18.2 |
dataseries Switzerland's Data Series in One Place | 0.2.0 | 0.2.0 |
datasets | 4.2.3 | 4.2.3 |
dataverse Client for Dataverse 4+ Repositories | 0.3.10 | 0.3.10 |
datawizard Easy Data Wrangling and Statistical Transformations | 0.4.0 | 0.4.0 |
date Functions for Handling Dates | 1.2-39 | 1.2-39 |
Davies The Davies Quantile Function | 1.2-0 | 1.2-0 |
dbfaker A Tool to Ensure the Validity of Database Writes | 0.1.0 | 0.1.0 |
DBI R Database Interface | 1.1.3 | 1.1.3 |
dblcens Compute the NPMLE of Distribution Function from Doubly Censored Data, Plus the Empirical Likelihood Ratio for F(T) | 1.1.9 | 1.1.9 |
dbmss Distance-Based Measures of Spatial Structures | 2.8-0 | 2.8-0 |
dbplyr A 'dplyr' Back End for Databases | 2.3.1 | 2.3.1 |
dbscan Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Related Algorithms | 1.1-11 | 1.1-11 |
dbstats Distance-Based Statistics | 2.0.1 | 2.0.1 |
dbx A Fast, Easy-to-Use Database Interface | 0.2.8 | 0.2.8 |
DChaos Chaotic Time Series Analysis | 0.1-6 | 0.1-6 |
DCluster Functions for the Detection of Spatial Clusters of Diseases | 0.2-8 | 0.2-8 |
dcov A Fast Implementation of Distance Covariance | 0.1.1 | 0.1.1 |
dCovTS Distance Covariance and Correlation for Time Series Analysis | 1.3 | 1.3 |
dcurver Utility Functions for Davidian Curves | 0.9.2 | 0.9.2 |
ddalpha Depth-Based Classification and Calculation of Data Depth | 1.3.13 | 1.3.13 |
ddCt | 1.52.0 | 1.52.0 |
DDD Diversity-Dependent Diversification | 5.2.1 | 5.2.1 |
dde Solve Delay Differential Equations | 1.0.1 | 1.0.1 |
ddsPLS Data-Driven Sparse Partial Least Squares Robust to Missing Samples for Mono and Multi-Block Data Sets | 1.1.4 | 1.1.4 |
deal Learning Bayesian Networks with Mixed Variables | 1.2-39 | 1.2-39 |
deBInfer Bayesian Inference for Differential Equations | 0.4.4 | 0.4.4 |
debugme Debug R Packages | 1.1.0 | 1.1.0 |
DeclareDesign Declare and Diagnose Research Designs | 0.30.0 | 0.30.0 |
decompr Global Value Chain Decomposition | 6.4.0 | 6.4.0 |
deducorrect Deductive Correction, Deductive Imputation, and Deterministic Correction | 1.3.7 | 1.3.7 |
deepnet Deep Learning Toolkit in R | 0.2.1 | 0.2.1 |
degreenet Models for Skewed Count Distributions Relevant to Networks | 1.3-3 | 1.3-3 |
Delaporte Statistical Functions for the Delaporte Distribution | 8.1.0 | 8.1.0 |
DelayedArray | 0.22.0 | 0.22.0 |
DelayedMatrixStats | 1.18.2 | 1.18.2 |
deldir Delaunay Triangulation and Dirichlet (Voronoi) Tessellation | 1.0-6 | 1.0-6 |
delt Estimation of Multivariate Densities Using Adaptive Partitions | 0.8.2 | 0.8.2 |
deltaPlotR Identification of Dichotomous Differential Item Functioning (DIF) using Angoff's Delta Plot Method | 1.6 | 1.6 |
demography Forecasting Mortality, Fertility, Migration and Population Data | 1.22 | 1.22 |
dendextend Extending 'dendrogram' Functionality in R | 1.16.0 | 1.16.0 |
denoiseR Regularized Low Rank Matrix Estimation | 1.0.2 | 1.0.2 |
denpro Visualization of Multivariate Functions, Sets, and Data | 0.9.2 | 0.9.2 |
denseFLMM Functional Linear Mixed Models for Densely Sampled Data | 0.1.2 | 0.1.2 |
densEstBayes Density Estimation via Bayesian Inference Engines | 1.0-2.1 | 1.0-2.1 |
denstrip Density Strips and Other Methods for Compactly Illustrating Distributions | 1.5.4 | 1.5.4 |
DEoptim Global Optimization by Differential Evolution | 2.2-8 | 2.2-8 |
DEoptimR Differential Evolution Optimization in Pure R | 1.0-11 | 1.0-11 |
depmix Dependent Mixture Models | 0.9.16 | 0.9.16 |
depmixS4 Dependent Mixture Models - Hidden Markov Models of GLMs and Other Distributions in S4 | 1.5-0 | 1.5-0 |
DepthProc Statistical Depth Functions for Multivariate Analysis | 2.1.5 | 2.1.5 |
Deriv Symbolic Differentiation | 4.1.3 | 4.1.3 |
derivmkts Functions and R Code to Accompany Derivatives Markets | 0.2.5 | 0.2.5 |
desc Manipulate DESCRIPTION Files | 1.4.1 | 1.4.1 |
DescTools Tools for Descriptive Statistics | 0.99.48 | 0.99.48 |
deseasonalize Optimal deseasonalization for geophysical time series using AR<U+000a>fitting | 1.35 | 1.35 |
DESeq2 | 1.36.0 | 1.36.0 |
DesignLibrary Library of Research Designs | 0.1.10 | 0.1.10 |
desirability Function Optimization and Ranking via Desirability Functions | 2.1 | 2.1 |
deSolve Solvers for Initial Value Problems of Differential Equations ('ODE', 'DAE', 'DDE') | 1.35 | 1.35 |
details Create Details HTML Tag for Markdown and Package Documentation | 0.3.0 | 0.3.0 |
detpack Density Estimation and Random Number Generation with Distribution Element Trees | 1.1.3 | 1.1.3 |
devtools Tools to Make Developing R Packages Easier | 2.4.3 | 2.4.3 |
dexter Data Management and Analysis of Tests | 1.2.2 | 1.2.2 |
dexterMST CML and Bayesian Calibration of Multistage Tests | 0.9.3 | 0.9.3 |
dfcrm Dose-Finding by the Continual Reassessment Method | 0.2-2.1 | 0.2-2.1 |
dfidx Indexed Data Frames | 0.0-5 | 0.0-5 |
DFIT Differential Functioning of Items and Tests | 1.1 | 1.1 |
dfmeta Meta-Analysis of Phase I Dose-Finding Early Clinical Trials | 1.0.0 | 1.0.0 |
dfoptim Derivative-Free Optimization | 2020.10-1 | 2020.10-1 |
dggridR Discrete Global Grids | 2.0.4 | 2.0.4 |
dglm Double Generalized Linear Models | 1.8.4 | 1.8.4 |
DHARMa Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models | 0.4.5 | 0.4.5 |
DHS.rates Calculates Demographic Indicators | 0.9.1 | 0.9.1 |
diagis Diagnostic Plot and Multivariate Summary Statistics of Weighted Samples from Importance Sampling | 0.2.2 | 0.2.2 |
diagmeta Meta-Analysis of Diagnostic Accuracy Studies with Several Cutpoints | 0.5-0 | 0.5-0 |
diagonals Block Diagonal Extraction or Replacement | 6.4.0 | 6.4.0 |
diagram Functions for Visualising Simple Graphs (Networks), Plotting Flow Diagrams | 1.6.5 | 1.6.5 |
DiagrammeR Graph/Network Visualization | 1.0.9 | 1.0.9 |
DiagrammeRsvg Export DiagrammeR Graphviz Graphs as SVG | 0.1 | 0.1 |
dials Tools for Creating Tuning Parameter Values | 0.1.1 | 0.1.1 |
DiceDesign Designs of Computer Experiments | 1.9 | 1.9 |
DiceKriging Kriging Methods for Computer Experiments | 1.6.0 | 1.6.0 |
dichromat Color Schemes for Dichromats | 2.0-0.1 | 2.0-0.1 |
dictionar6 R6 Dictionary Interface | 0.1.3 | 0.1.3 |
dielectric Defines some physical constants and dielectric functions<U+000a>commonly used in optics, plasmonics. | 0.2.3 | 0.2.3 |
DIFboost Detection of Differential Item Functioning (DIF) in Rasch Models by Boosting Techniques | 0.3 | 0.3 |
diffeqr Solving Differential Equations (ODEs, SDEs, DDEs, DAEs) | 1.1.3 | 1.1.3 |
diffobj Diffs for R Objects | 0.3.5 | 0.3.5 |
DiffusionRimp Inference and Analysis for Diffusion Processes via Data Imputation and Method of Lines | 0.1.2 | 0.1.2 |
DIFlasso A Penalty Approach to Differential Item Functioning in Rasch Models | 1.0-4 | 1.0-4 |
difNLR DIF and DDF Detection by Non-Linear Regression Models | 1.4.1 | 1.4.1 |
difR Collection of Methods to Detect Dichotomous Differential Item Functioning (DIF) | 5.1 | 5.1 |
DIFtree Item Focussed Trees for the Identification of Items in Differential Item Functioning | 3.1.6 | 3.1.6 |
digest Create Compact Hash Digests of R Objects | 0.6.30 | 0.6.30 |
dils Data-Informed Link Strength. Combine multiple-relationship<U+000a>networks into a single weighted network. Impute (fill-in)<U+000a>missing network links. | 0.8.1 | 0.8.1 |
dimensionsR Gathering Bibliographic Records from 'Digital Science Dimensions' Using 'DSL' API | 0.0.3 | 0.0.3 |
dimRed A Framework for Dimensionality Reduction | 0.2.5 | 0.2.5 |
dina Bayesian Estimation of DINA Model | 2.0.0 | 2.0.0 |
diptest Hartigan's Dip Test Statistic for Unimodality - Corrected | 0.76-0 | 0.76-0 |
Dire Linear Regressions with a Latent Outcome Variable | 2.1.1 | 2.1.1 |
Directional A Collection of Functions for Directional Data Analysis | 5.8 | 5.8 |
directlabels Direct Labels for Multicolor Plots | 2021.1.13 | 2021.1.13 |
dirichletprocess Build Dirichlet Process Objects for Bayesian Modelling | 0.4.0 | 0.4.0 |
dirmult Estimation in Dirichlet-Multinomial Distribution | 0.1.3-5 | 0.1.3-5 |
discgolf Discourse API Client | 0.2.0 | 0.2.0 |
disclap Discrete Laplace Exponential Family | 1.5.1 | 1.5.1 |
discretecdAlgorithm Coordinate-Descent Algorithm for Learning Sparse Discrete Bayesian Networks | 0.0.7 | 0.0.7 |
DiscreteInverseWeibull Discrete Inverse Weibull Distribution | 1.0.2 | 1.0.2 |
DiscreteLaplace Discrete Laplace Distributions | 1.1.1 | 1.1.1 |
DiscreteWeibull Discrete Weibull Distributions (Type 1 and 3) | 1.1 | 1.1 |
discretization Data Preprocessing, Discretization for Classification | 1.0-1.1 | 1.0-1.1 |
DiscriMiner Tools of the Trade for Discriminant Analysis | 0.1-29 | 0.1-29 |
discSurv Discrete Time Survival Analysis | 2.0.0 | 2.0.0 |
diseasemapping Modelling Spatial Variation in Disease Risk for Areal Data | 1.5.1 | 1.5.1 |
dismo Species Distribution Modeling | 1.3-9 | 1.3-9 |
disordR Non-Ordered Vectors | 0.9 | 0.9 |
dispmod Modelling Dispersion in GLM | 1.2 | 1.2 |
dispRity Measuring Disparity | 1.7.0 | 1.7.0 |
Distance Distance Sampling Detection Function and Abundance Estimation | 1.0.7 | 1.0.7 |
distances Tools for Distance Metrics | 0.1.9 | 0.1.9 |
DistatisR DiSTATIS Three Way Metric Multidimensional Scaling | 1.0.1 | 1.0.1 |
distcrete Discrete Distribution Approximations | 1.0.3 | 1.0.3 |
distillery Method Functions for Confidence Intervals and to Distill Information from an Object | 1.2-1 | 1.2-1 |
distory Distance Between Phylogenetic Histories | 1.4.4 | 1.4.4 |
distr Object Oriented Implementation of Distributions | 2.9.1 | 2.9.1 |
distr6 The Complete R6 Probability Distributions Interface | 1.6.9 | 1.6.9 |
distrDoc Documentation for 'distr' Family of R Packages | 2.8.1 | 2.8.1 |
distrEllipse S4 Classes for Elliptically Contoured Distributions | 2.8.1 | 2.8.1 |
distrEx Extensions of Package 'distr' | 2.9.0 | 2.9.0 |
distributional Vectorised Probability Distributions | 0.3.1 | 0.3.1 |
distributions3 Probability Distributions as S3 Objects | 0.2.1 | 0.2.1 |
DistributionUtils Distribution Utilities | 0.6-0 | 0.6-0 |
distrMod Object Oriented Implementation of Probability Models | 2.9.0 | 2.9.0 |
distrom Distributed Multinomial Regression | 1.0.1 | 1.0.1 |
distrSim Simulation Classes Based on Package 'distr' | 2.8.1 | 2.8.1 |
distrTeach Extensions of Package 'distr' for Teaching Stochastics/Statistics in Secondary School | 2.9.0 | 2.9.0 |
distrTEst Estimation and Testing Classes Based on Package 'distr' | 2.8.1 | 2.8.1 |
distTails A Collection of Full Defined Distribution Tails | 0.1.2 | 0.1.2 |
diveMove Dive Analysis and Calibration | 1.6.0 | 1.6.0 |
diversitree Comparative 'Phylogenetic' Analyses of Diversification | 0.9-16 | 0.9-16 |
divest Get Images Out of DICOM Format Quickly | 0.10.3 | 0.10.3 |
diyar Record Linkage and Epidemiological Case Definitions in R | 0.4.1 | 0.4.1 |
dLagM Time Series Regression Models with Distributed Lag Models | 1.1.8 | 1.1.8 |
dlm Bayesian and Likelihood Analysis of Dynamic Linear Models | 1.1-6 | 1.1-6 |
dlmap Detection Localization Mapping for QTL | 1.13 | 1.13 |
dlnm Distributed Lag Non-Linear Models | 2.4.7 | 2.4.7 |
dlookr Tools for Data Diagnosis, Exploration, Transformation | 0.6.1 | 0.6.1 |
dlstats Download Stats of R Packages | 0.1.5 | 0.1.5 |
dMod Dynamic Modeling and Parameter Estimation in ODE Models | 1.0.2 | 1.0.2 |
DMwR Functions and data for "Data Mining with R" | 0.4.1 | 0.4.1 |
dng Distributions and Gradients | 0.2.1 | 0.2.1 |
doBy Groupwise Statistics, LSmeans, Linear Estimates, Utilities | 4.6.16 | 4.6.16 |
docopt Command-Line Interface Specification Language | 0.7.1 | 0.7.1 |
docuSignr Connect to 'DocuSign' API | 0.0.3 | 0.0.3 |
dodgr Distances on Directed Graphs | 0.2.13 | 0.2.13 |
DoE.base Full Factorials, Orthogonal Arrays and Base Utilities for DoE Packages | 1.2-1 | 1.2-1 |
DoE.wrapper Wrapper Package for Design of Experiments Functionality | 0.11 | 0.11 |
doFuture Use Foreach to Parallelize via the Future Framework | 0.12.2 | 0.12.2 |
doMC Foreach Parallel Adaptor for 'parallel' | 1.3.8 | 1.3.8 |
domino R Console Bindings for the 'Domino Command-Line Client' | 0.3.1 | 0.3.1 |
doMPI Foreach Parallel Adaptor for the Rmpi Package | 0.2.2 | 0.2.2 |
doParallel Foreach Parallel Adaptor for the 'parallel' Package | 1.0.17 | 1.0.17 |
doRedis 'Foreach' Parallel Adapter Using the 'Redis' Database | 3.0.1 | 3.0.1 |
doRNG Generic Reproducible Parallel Backend for 'foreach' Loops | 1.8.6 | 1.8.6 |
DoseFinding Planning and Analyzing Dose Finding Experiments | 1.0-2 | 1.0-2 |
doSNOW Foreach Parallel Adaptor for the 'snow' Package | 1.0.20 | 1.0.20 |
dosresmeta Multivariate Dose-Response Meta-Analysis | 2.0.1 | 2.0.1 |
dotCall64 Enhanced Foreign Function Interface Supporting Long Vectors | 1.0-2 | 1.0-2 |
dotwhisker Dot-and-Whisker Plots of Regression Results | 0.7.4 | 0.7.4 |
Dowd Functions Ported from 'MMR2' Toolbox Offered in Kevin Dowd's Book Measuring Market Risk | 0.12 | 0.12 |
downlit Syntax Highlighting and Automatic Linking | 0.4.0 | 0.4.0 |
downloader Download Files over HTTP and HTTPS | 0.4 | 0.4 |
dparser Port of 'Dparser' Package | 1.3.1-10 | 1.3.1-10 |
dplyr A Grammar of Data Manipulation | 1.1.0 | 1.1.0 |
dqrng Fast Pseudo Random Number Generators | 0.3.0 | 0.3.0 |
dr Methods for Dimension Reduction for Regression | 3.0.10 | 3.0.10 |
drake A Pipeline Toolkit for Reproducible Computation at Scale | 7.13.4 | 7.13.4 |
dreamerr Error Handling Made Easy | 1.2.3 | 1.2.3 |
drgee Doubly Robust Generalized Estimating Equations | 1.1.10 | 1.1.10 |
DriftBurstHypothesis Calculates the Test-Statistic for the Drift Burst Hypothesis | 0.4.0.1 | 0.4.0.1 |
driftR Drift Correcting Water Quality Data | 1.1.0 | 1.1.0 |
DrImpute Imputing Dropout Events in Single-Cell RNA-Sequencing Data | 1.0 | 1.0 |
DRR Dimensionality Reduction via Regression | 0.0.4 | 0.0.4 |
dsa Seasonal Adjustment of Daily Time Series | 1.0.12 | 1.0.12 |
dse Dynamic Systems Estimation (Time Series Package) | 2020.2-1 | 2020.2-1 |
DSL Distributed Storage and List | 0.1-7 | 0.1-7 |
dslabs Data Science Labs | 0.7.4 | 0.7.4 |
DSpat Spatial Modelling for Distance Sampling Data | 0.1.6 | 0.1.6 |
DStree Recursive Partitioning for Discrete-Time Survival Trees | 1.0 | 1.0 |
DT A Wrapper of the JavaScript Library 'DataTables' | 0.27 | 0.27 |
DtD Distance to Default | 0.2.2 | 0.2.2 |
DTDA Doubly Truncated Data Analysis | 3.0.1 | 3.0.1 |
dtplyr Data Table Back-End for 'dplyr' | 1.3.0 | 1.3.0 |
dtt Discrete Trigonometric Transforms | 0.1-2 | 0.1-2 |
dtw Dynamic Time Warping Algorithms | 1.23-1 | 1.23-1 |
DTWBI Imputation of Time Series Based on Dynamic Time Warping | 1.1 | 1.1 |
dtwclust Time Series Clustering Along with Optimizations for the Dynamic Time Warping Distance | 5.5.12 | 5.5.12 |
DTWUMI Imputation of Multivariate Time Series Based on Dynamic Time Warping | 1.0 | 1.0 |
duckduckr Simple Client for the DuckDuckGo Instant Answer API | 1.0.0 | 1.0.0 |
durmod Mixed Proportional Hazard Competing Risk Model | 1.1-4 | 1.1-4 |
dvmisc Convenience Functions, Moving Window Statistics, and Graphics | 1.1.4 | 1.1.4 |
dygraphs Interface to 'Dygraphs' Interactive Time Series Charting Library | 1.1.1.6 | 1.1.1.6 |
Dykstra Quadratic Programming using Cyclic Projections | 1.0-0 | 1.0-0 |
dyn Time Series Regression | 0.2-9.6 | 0.2-9.6 |
dynamicGraph dynamicGraph | 0.2.2.6 | 0.2.2.6 |
dynamichazard Dynamic Hazard Models using State Space Models | 1.0.1 | 1.0.1 |
dynamicTreeCut Methods for Detection of Clusters in Hierarchical Clustering Dendrograms | 1.63-1 | 1.63-1 |
dynatopmodel Implementation of the Dynamic TOPMODEL Hydrological Model | 1.2.1 | 1.2.1 |
dynfrail Fitting Dynamic Frailty Models with the EM Algorithm | 0.5.2 | 0.5.2 |
dynlm Dynamic Linear Regression | 0.3-6 | 0.3-6 |
dynpred Companion Package to "Dynamic Prediction in Clinical Survival Analysis" | 0.1.2 | 0.1.2 |
dynsurv Dynamic Models for Survival Data | 0.4-3 | 0.4-3 |
e1071 Misc Functions of the Department of Statistics, Probability Theory Group (Formerly: E1071), TU Wien | 1.7-13 | 1.7-13 |
eaf Plots of the Empirical Attainment Function | 2.3 | 2.3 |
earlywarnings Early Warning Signals for Critical Transitions in Time Series | 1.0.59 | 1.0.59 |
earth Multivariate Adaptive Regression Splines | 5.3.2 | 5.3.2 |
easycsv Load Multiple 'csv' and 'txt' Tables | 1.0.8 | 1.0.8 |
easySdcTable Easy Interface to the Statistical Disclosure Control Package 'sdcTable' Extended with Own Implementation of 'GaussSuppression' | 1.0.3 | 1.0.3 |
eba Elimination-by-Aspects Models | 1.10-0 | 1.10-0 |
EbayesThresh Empirical Bayes Thresholding and Related Methods | 1.4-12 | 1.4-12 |
ebdbNet Empirical Bayes Estimation of Dynamic Bayesian Networks | 1.2.6 | 1.2.6 |
ecb Programmatic Access to the European Central Bank's Statistical Data Warehouse | 0.4.0 | 0.4.0 |
ecd Elliptic Lambda Distribution and Option Pricing Model | 0.9.2.4 | 0.9.2.4 |
Ecdat Data Sets for Econometrics | 0.4-0 | 0.4-0 |
ecespa Functions for Spatial Point Pattern Analysis | 1.1-17 | 1.1-17 |
Ecfun Functions for 'Ecdat' | 0.3-1 | 0.3-1 |
eChem Simulations for Electrochemistry Experiments | 1.0.0 | 1.0.0 |
echor Access EPA 'ECHO' Data | 0.1.7 | 0.1.7 |
ECLRMC Ensemble Correlation-Based Low-Rank Matrix Completion | 1.0 | 1.0 |
ecm Build Error Correction Models | 6.3.0 | 6.3.0 |
ecodist Dissimilarity-Based Functions for Ecological Analysis | 2.0.9 | 2.0.9 |
Ecohydmod Ecohydrological Modelling | 1.0.0 | 1.0.0 |
EcoHydRology A Community Modeling Foundation for Eco-Hydrology | 0.4.12.1 | 0.4.12.1 |
ecolMod "A Practical Guide to Ecological Modelling - Using R as a Simulation Platform" | 1.2.6.4 | 1.2.6.4 |
ecoreg Ecological Regression using Aggregate and Individual Data | 0.2.3 | 0.2.3 |
ECOSolveR Embedded Conic Solver in R | 0.5.4 | 0.5.4 |
ecoval Procedures for Ecological Assessment of Surface Waters | 1.2.9 | 1.2.9 |
ecp Non-Parametric Multiple Change-Point Analysis of Multivariate Data | 3.1.3 | 3.1.3 |
ecr Evolutionary Computation in R | 2.1.1 | 2.1.1 |
edci Edge Detection and Clustering in Images | 1.1-3 | 1.1-3 |
edfReader Reading EDF(+) and BDF(+) Files | 1.2.1 | 1.2.1 |
edgeR | 3.38.0 | 3.38.0 |
editData 'RStudio' Addin for Editing a 'data.frame' | 0.1.8 | 0.1.8 |
EditImputeCont Simultaneous Edit-Imputation for Continuous Microdata | 1.1.6 | 1.1.6 |
editrules Parsing, Applying, and Manipulating Data Cleaning Rules | 2.9.3 | 2.9.3 |
EdSurvey Analysis of NCES Education Survey and Assessment Data | 3.0.2 | 3.0.2 |
eegkit Toolkit for Electroencephalography Data | 1.0-4 | 1.0-4 |
eegkitdata Electroencephalography Toolkit Datasets | 1.1 | 1.1 |
EEM Read and Preprocess Fluorescence Excitation-Emission Matrix (EEM) Data | 1.1.1 | 1.1.1 |
EFAutilities Utility Functions for Exploratory Factor Analysis | 2.1.2 | 2.1.2 |
effects Effect Displays for Linear, Generalized Linear, and Other Models | 4.2-2 | 4.2-2 |
effectsize Indices of Effect Size | 0.8.3 | 0.8.3 |
effsize Efficient Effect Size Computation | 0.8.1 | 0.8.1 |
EGAnet Exploratory Graph Analysis – a Framework for Estimating the Number of Dimensions in Multivariate Data using Network Psychometrics | 1.0.0 | 1.0.0 |
egcm Engle-Granger Cointegration Models | 1.0.12 | 1.0.12 |
EGRET Exploration and Graphics for RivEr Trends | 3.0.8 | 3.0.8 |
EGRETci Exploration and Graphics for RivEr Trends Confidence Intervals | 2.0.4 | 2.0.4 |
eha Event History Analysis | 2.10.3 | 2.10.3 |
ei Ecological Inference | 1.3-3 | 1.3-3 |
EIAdata R Wrapper for the Energy Information Administration (EIA) API | 0.1.3 | 0.1.3 |
eigeninv Generates (dense) matrices that have a given set of eigenvalues | 2011.8-1 | 2011.8-1 |
eigenmodel Semiparametric Factor and Regression Models for Symmetric Relational Data | 1.11 | 1.11 |
EigenR Complex Matrix Algebra with 'Eigen' | 1.2.3 | 1.2.3 |
eiPack Ecological Inference and Higher-Dimension Data Management | 0.2-1 | 0.2-1 |
elastic General Purpose Interface to 'Elasticsearch' | 1.2.0 | 1.2.0 |
elasticIsing Ising Network Estimation using Elastic Net and k-Fold Cross-Validation | 0.2 | 0.2 |
elasticnet Elastic-Net for Sparse Estimation and Sparse PCA | 1.3 | 1.3 |
elevatr Access Elevation Data from Various APIs | 0.4.2 | 0.4.2 |
ellipse Functions for Drawing Ellipses and Ellipse-Like Confidence Regions | 0.4.3 | 0.4.3 |
ellipsis Tools for Working with ... | 0.3.2 | 0.3.2 |
elliptic Weierstrass and Jacobi Elliptic Functions | 1.4-0 | 1.4-0 |
ELYP Empirical Likelihood Analysis for the Cox Model and Yang-Prentice (2005) Model | 0.7-5 | 0.7-5 |
EMbC Expectation-Maximization Binary Clustering | 2.0.3 | 2.0.3 |
EMCluster EM Algorithm for Model-Based Clustering of Finite Mixture Gaussian Distribution | 0.2-14 | 0.2-14 |
EMD Empirical Mode Decomposition and Hilbert Spectral Analysis | 1.5.9 | 1.5.9 |
emdbook Support Functions and Data for "Ecological Models and Data" | 1.3.12 | 1.3.12 |
emdi Estimating and Mapping Disaggregated Indicators | 2.1.3 | 2.1.3 |
emg Exponentially Modified Gaussian (EMG) Distribution | 1.0.9 | 1.0.9 |
emIRT EM Algorithms for Estimating Item Response Theory Models | 0.0.13 | 0.0.13 |
emmeans Estimated Marginal Means, aka Least-Squares Means | 1.8.5 | 1.8.5 |
emoa Evolutionary Multiobjective Optimization Algorithms | 0.5-0.1 | 0.5-0.1 |
empichar Evaluates the Empirical Characteristic Function for Multivariate Samples | 1.0.0 | 1.0.0 |
emplik Empirical Likelihood Ratio for Censored/Truncated Data | 1.2 | 1.2 |
emplik2 Empirical Likelihood Ratio Test for Two Samples with Censored Data | 1.32 | 1.32 |
emulator Bayesian Emulation of Computer Programs | 1.2-21 | 1.2-21 |
energy E-Statistics: Multivariate Inference via the Energy of Data | 1.7-10 | 1.7-10 |
english Translate Integers into English | 1.2-6 | 1.2-6 |
ENMeval Automated Tuning and Evaluations of Ecological Niche Models | 2.0.0 | 2.0.0 |
enpls Ensemble Partial Least Squares Regression | 6.1 | 6.1 |
enrichR Provides an R Interface to 'Enrichr' | 3.0 | 3.0 |
enrichwith Methods to Enrich R Objects with Extra Components | 0.3.1 | 0.3.1 |
ensembldb | 2.20.1 | 2.20.1 |
ensembleBMA Probabilistic Forecasting using Ensembles and Bayesian Model Averaging | 5.1.8 | 5.1.8 |
entropart Entropy Partitioning to Measure Diversity | 1.6-10 | 1.6-10 |
entropy Estimation of Entropy, Mutual Information and Related Quantities | 1.3.1 | 1.3.1 |
EntropyEstimation Estimation of Entropy and Related Quantities | 1.2 | 1.2 |
EntropyMCMC MCMC Simulation and Convergence Evaluation using Entropy and Kullback-Leibler Divergence Estimation | 1.0.4 | 1.0.4 |
enveomics.R Various Utilities for Microbial Genomics and Metagenomics | 1.9.0 | 1.9.0 |
envnames Keep Track of User-Defined Environment Names | 0.4.1 | 0.4.1 |
EnvStats Package for Environmental Statistics, Including US EPA Guidance | 2.7.0 | 2.7.0 |
Epi Statistical Analysis in Epidemiology | 2.47 | 2.47 |
epibasix Elementary Epidemiological Functions for Epidemiology and Biostatistics | 1.5 | 1.5 |
epiR Tools for the Analysis of Epidemiological Data | 2.0.58 | 2.0.58 |
episensr Basic Sensitivity Analysis of Epidemiological Results | 1.1.0 | 1.1.0 |
epitools Epidemiology Tools | 0.5-10.1 | 0.5-10.1 |
equate Observed-Score Linking and Equating | 2.0.8 | 2.0.8 |
equateIRT IRT Equating Methods | 2.3.0 | 2.3.0 |
equateMultiple Equating of Multiple Forms | 0.1.1 | 0.1.1 |
equivalence Provides Tests and Graphics for Assessing Tests of Equivalence | 0.7.2 | 0.7.2 |
equSA Learning High-Dimensional Graphical Models | 1.2.1 | 1.2.1 |
ercv Fitting Tails by the Empirical Residual Coefficient of Variation | 1.0.1 | 1.0.1 |
erer Empirical Research in Economics with R | 3.1 | 3.1 |
ergm Fit, Simulate and Diagnose Exponential-Family Models for Networks | 4.4.0 | 4.4.0 |
ergm.count Fit, Simulate and Diagnose Exponential-Family Models for Networks with Count Edges | 4.1.1 | 4.1.1 |
eRm Extended Rasch Modeling | 1.0-2 | 1.0-2 |
err Customizable Object Sensitive Messages | 0.2.0 | 0.2.0 |
errorlocate Locate Errors with Validation Rules | 1.1 | 1.1 |
errors Uncertainty Propagation for R Vectors | 0.4.0 | 0.4.0 |
es.dif Compute Effect Sizes of the Difference | 1.0.2 | 1.0.2 |
esaBcv Estimate Number of Latent Factors and Factor Matrix for Factor Analysis | 1.2.1.1 | 1.2.1.1 |
esc Effect Size Computation for Meta Analysis | 0.5.1 | 0.5.1 |
ESG A Package for Asset Projection | 1.2 | 1.2 |
EstCRM Calibrating Parameters for the Samejima's Continuous IRT Model | 1.6 | 1.6 |
estimability Tools for Assessing Estimability of Linear Predictions | 1.4.1 | 1.4.1 |
estimatr Fast Estimators for Design-Based Inference | 1.0.0 | 1.0.0 |
estmeansd Estimating the Sample Mean and Standard Deviation from Commonly Reported Quantiles in Meta-Analysis | 1.0.0 | 1.0.0 |
estudy2 An Implementation of Parametric and Nonparametric Event Study | 0.10.0 | 0.10.0 |
etm Empirical Transition Matrix | 1.1.1 | 1.1.1 |
etma Epistasis Test in Meta-Analysis | 1.1-1 | 1.1-1 |
europepmc R Interface to the Europe PubMed Central RESTful Web Service | 0.4.1 | 0.4.1 |
eurostat Tools for Eurostat Open Data | 3.7.10 | 3.7.10 |
EvalEst Dynamic Systems Estimation - Extensions | 2021.2-1 | 2021.2-1 |
evaluate Parsing and Evaluation Tools that Provide More Details than the Default | 0.20 | 0.20 |
EValue Sensitivity Analyses for Unmeasured Confounding and Other Biases in Observational Studies and Meta-Analyses | 4.1.3 | 4.1.3 |
Evapotranspiration Modelling Actual, Potential and Reference Crop Evapotranspiration | 1.16 | 1.16 |
evclass Evidential Distance-Based Classification | 2.0.0 | 2.0.0 |
evclust Evidential Clustering | 2.0.2 | 2.0.2 |
evd Functions for Extreme Value Distributions | 2.3-6 | 2.3-6 |
evdbayes Bayesian Analysis in Extreme Value Theory | 1.1-1 | 1.1-1 |
events Store and manipulate event data | 0.5 | 0.5 |
evgam Generalised Additive Extreme Value Models | 1.0.0 | 1.0.0 |
evir Extreme Values in R | 1.7-4 | 1.7-4 |
evmix Extreme Value Mixture Modelling, Threshold Estimation and Boundary Corrected Kernel Density Estimation | 2.12 | 2.12 |
evobiR Comparative and Population Genetic Analyses | 1.1 | 1.1 |
evtree Evolutionary Learning of Globally Optimal Trees | 1.0-8 | 1.0-8 |
ewoc Escalation with Overdose Control | 0.3.0 | 0.3.0 |
Exact Unconditional Exact Test | 3.2 | 3.2 |
exactextractr Fast Extraction from Raster Datasets using Polygons | 0.4.0 | 0.4.0 |
exactLoglinTest Monte Carlo Exact Tests for Log-linear models | 1.4.2 | 1.4.2 |
exactmeta Exact fixed effect meta analysis | 1.0-2 | 1.0-2 |
exactRankTests Exact Distributions for Rank and Permutation Tests | 0.8-35 | 0.8-35 |
exams Automatic Generation of Exams in R | 2.4-0 | 2.4-0 |
ExceedanceTools Confidence/Credible Regions for Exceedance Sets and Contour Lines | 1.3.4 | 1.3.4 |
exdex Estimation of the Extremal Index | 1.2.1 | 1.2.1 |
experiment R Package for Designing and Analyzing Randomized Experiments | 1.2.1 | 1.2.1 |
expint Exponential Integral and Incomplete Gamma Function | 0.1-8 | 0.1-8 |
expm Matrix Exponential, Log, 'etc' | 0.999-7 | 0.999-7 |
ExPosition Exploratory Analysis with the Singular Value Decomposition | 2.8.23 | 2.8.23 |
expsmooth Data Sets from "Forecasting with Exponential Smoothing" | 2.3 | 2.3 |
exreport Fast, Reliable and Elegant Reproducible Research | 0.4.1 | 0.4.1 |
extfunnel Additional Funnel Plot Augmentations | 1.3 | 1.3 |
extraDistr Additional Univariate and Multivariate Distributions | 1.9.1 | 1.9.1 |
extrafont Tools for Using Fonts | 0.19 | 0.19 |
extrafontdb Package for holding the database for the extrafont package | 1.0 | 1.0 |
extras Helper Functions for Bayesian Analyses | 0.5.0 | 0.5.0 |
ExtremeBounds Extreme Bounds Analysis (EBA) | 0.1.6 | 0.1.6 |
extremefit Estimation of Extreme Conditional Quantiles and Probabilities | 1.0.2 | 1.0.2 |
extRemes Extreme Value Analysis | 2.1-3 | 2.1-3 |
extremeStat Extreme Value Statistics and Quantile Estimation | 1.5.3 | 1.5.3 |
extremevalues Univariate Outlier Detection | 2.3.3 | 2.3.3 |
exuber Econometric Analysis of Explosive Time Series | 0.4.2 | 0.4.2 |
eyelinker Import ASC Files from EyeLink Eye Trackers | 0.2.1 | 0.2.1 |
eyetracking Eyetracking Helper Functions | 1.1 | 1.1 |
eyetrackingR Eye-Tracking Data Analysis | 0.2.0 | 0.2.0 |
ez Easy Analysis and Visualization of Factorial Experiments | 4.4-0 | 4.4-0 |
ezsim provide an easy to use framework to conduct simulation | 0.5.5 | 0.5.5 |
fable Forecasting Models for Tidy Time Series | 0.3.2 | 0.3.2 |
fabletools Core Tools for Packages in the 'fable' Framework | 0.3.2 | 0.3.2 |
fabricatr Imagine Your Data Before You Collect It | 0.16.0 | 0.16.0 |
FactoClass Combination of Factorial Methods and Cluster Analysis | 1.2.7 | 1.2.7 |
factoextra Extract and Visualize the Results of Multivariate Data Analyses | 1.0.7 | 1.0.7 |
FactoMineR Multivariate Exploratory Data Analysis and Data Mining | 2.6 | 2.6 |
factorQR Bayesian quantile regression factor models | 0.1-4 | 0.1-4 |
factorstochvol Bayesian Estimation of (Sparse) Latent Factor Stochastic Volatility Models | 1.0.1 | 1.0.1 |
factualR thin wrapper for the Factual.com server API | 0.5 | 0.5 |
FAdist Distributions that are Sometimes Used in Hydrology | 2.4 | 2.4 |
fail File Abstraction Interface Layer (FAIL) | 1.3 | 1.3 |
fairml Fair Models in Machine Learning | 0.6.3 | 0.6.3 |
fairmodels Flexible Tool for Bias Detection, Visualization, and Mitigation | 1.2.0 | 1.2.0 |
fame Interface for FAME Time Series Database | 2.21.1 | 2.21.1 |
FamEvent Family Age-at-Onset Data Simulation and Penetrance Estimation | 3.0 | 3.0 |
fANCOVA Nonparametric Analysis of Covariance | 0.6-1 | 0.6-1 |
fanplot Visualisation of Sequential Probability Distributions Using Fan Charts | 4.0.0 | 4.0.0 |
fansi ANSI Control Sequence Aware String Functions | 1.0.4 | 1.0.4 |
FAOSTAT Download Data from the FAOSTAT Database | 2.2.4 | 2.2.4 |
faoutlier Influential Case Detection Methods for Factor Analysis and Structural Equation Models | 0.7.6 | 0.7.6 |
faraway Functions and Datasets for Books by Julian Faraway | 1.0.8 | 1.0.8 |
farver High Performance Colour Space Manipulation | 2.1.1 | 2.1.1 |
fAsianOptions Rmetrics - EBM and Asian Option Valuation | 3042.82 | 3042.82 |
fAssets Rmetrics - Analysing and Modelling Financial Assets | 3042.84 | 3042.84 |
fasstr Analyze, Summarize, and Visualize Daily Streamflow Data | 0.5.0 | 0.5.0 |
fast Implementation of the Fourier Amplitude Sensitivity Test (FAST) | 0.64 | 0.64 |
fastcluster Fast Hierarchical Clustering Routines for R and 'Python' | 1.2.3 | 1.2.3 |
fastcox Lasso and Elastic-Net Penalized Cox's Regression in High Dimensions Models using the Cocktail Algorithm | 1.1.3 | 1.1.3 |
fastDummies Fast Creation of Dummy (Binary) Columns and Rows from Categorical Variables | 1.6.3 | 1.6.3 |
fastGHQuad Fast 'Rcpp' Implementation of Gauss-Hermite Quadrature | 1.0.1 | 1.0.1 |
fastICA FastICA Algorithms to Perform ICA and Projection Pursuit | 1.2-3 | 1.2-3 |
fastLink Fast Probabilistic Record Linkage with Missing Data | 0.6.0 | 0.6.0 |
fastmap Fast Data Structures | 1.1.1 | 1.1.1 |
fastmatch Fast 'match()' Function | 1.1-3 | 1.1-3 |
fastpseudo Fast Pseudo Observations | 0.1 | 0.1 |
FastRWeb Fast Interactive Framework for Web Scripting Using R | 1.2-0 | 1.2-0 |
fastshap Fast Approximate Shapley Values | 0.0.7 | 0.0.7 |
fasttime Fast Utility Function for Time Parsing and Conversion | 1.1-0 | 1.1-0 |
FateID Quantification of Fate Bias in Multipotent Progenitors | 0.2.1 | 0.2.1 |
FatTailsR Kiener Distributions and Fat Tails in Finance | 1.8-0 | 1.8-0 |
fauxpas HTTP Error Helpers | 0.5.0 | 0.5.0 |
fBasics Rmetrics - Markets and Basic Statistics | 4022.94 | 4022.94 |
FBFsearch Algorithm for Searching the Space of Gaussian Directed Acyclic Graph Models Through Moment Fractional Bayes Factors | 1.2 | 1.2 |
fbRads Analyzing and Managing Facebook Ads from R | 0.2 | 0.2 |
fclust Fuzzy Clustering | 2.1.1.1 | 2.1.1.1 |
fCopulae Rmetrics - Bivariate Dependence Structures with Copulae | 4022.85 | 4022.85 |
FD Measuring Functional Diversity (FD) from Multiple Traits, and Other Tools for Functional Ecology | 1.0-12.1 | 1.0-12.1 |
fda Functional Data Analysis | 6.0.5 | 6.0.5 |
fda.usc Functional Data Analysis and Utilities for Statistical Computing | 2.1.0 | 2.1.0 |
fdaACF Autocorrelation Function for Functional Time Series | 1.0.0 | 1.0.0 |
fdadensity Functional Data Analysis for Density Functions by Transformation to a Hilbert Space | 0.1.2 | 0.1.2 |
fdakma Functional Data Analysis: K-Mean Alignment | 1.2.1 | 1.2.1 |
fdapace Functional Data Analysis and Empirical Dynamics | 0.5.9 | 0.5.9 |
fdasrvf Elastic Functional Data Analysis | 2.0.1 | 2.0.1 |
fdatest Interval Testing Procedure for Functional Data | 2.1.1 | 2.1.1 |
FDboost Boosting Functional Regression Models | 1.1-1 | 1.1-1 |
fdcov Analysis of Covariance Operators | 1.1.0 | 1.1.0 |
fdrtool Estimation of (Local) False Discovery Rates and Higher Criticism | 1.2.17 | 1.2.17 |
fds Functional Data Sets | 1.8 | 1.8 |
feasts Feature Extraction and Statistics for Time Series | 0.3.0 | 0.3.0 |
feather R Bindings to the Feather 'API' | 0.3.5 | 0.3.5 |
feature Local Inferential Feature Significance for Multivariate Kernel Density Estimation | 1.2.15 | 1.2.15 |
features Feature Extraction for Discretely-Sampled Functional Data | 2015.12-1 | 2015.12-1 |
fechner Fechnerian Scaling of Discrete Object Sets | 1.0-3 | 1.0-3 |
FedData Functions to Automate Downloading Geospatial Data Available from Several Federated Data Sources | 3.0.3 | 3.0.3 |
FeedbackTS Analysis of Feedback in Time Series | 1.5 | 1.5 |
feedeR Read RSS, Atom and RDF Feeds | 0.0.10 | 0.0.10 |
feisr Estimating Fixed Effects Individual Slope Models | 1.3.0 | 1.3.0 |
fExtremes Rmetrics - Modelling Extreme Events in Finance | 4021.83 | 4021.83 |
ff Memory-Efficient Storage of Large Data on Disk and Fast Access Functions | 4.0.9 | 4.0.9 |
ffbase Basic Statistical Functions for Package 'ff' | 0.13.3 | 0.13.3 |
FFD Freedom from Disease | 1.0-9 | 1.0-9 |
FField Force field simulation for a set of points | 0.1.0 | 0.1.0 |
fftw Fast FFT and DCT Based on the FFTW Library | 1.0-7 | 1.0-7 |
fftwtools Wrapper for 'FFTW3' Includes: One-Dimensional, Two-Dimensional, Three-Dimensional, and Multivariate Transforms | 0.9-11 | 0.9-11 |
fgac Generalized Archimedean Copula | 0.6-1 | 0.6-1 |
fGarch Rmetrics - Autoregressive Conditional Heteroskedastic Modelling | 4022.89 | 4022.89 |
FHDI Fractional Hot Deck and Fully Efficient Fractional Imputation | 1.4.1 | 1.4.1 |
FHtest Tests for Right and Interval-Censored Survival Data Based on the Fleming-Harrington Class | 1.5 | 1.5 |
fields Tools for Spatial Data | 14.1 | 14.1 |
FieldSim Random Fields (and Bridges) Simulations | 3.2.1 | 3.2.1 |
fiery A Lightweight and Flexible Web Framework | 1.2.0 | 1.2.0 |
filehash Simple Key-Value Database | 2.4-3 | 2.4-3 |
filehashSQLite Simple Key-Value Database Using SQLite | 0.2-6 | 0.2-6 |
filelock Portable File Locking | 1.0.2 | 1.0.2 |
filling Matrix Completion, Imputation, and Inpainting Methods | 0.2.3 | 0.2.3 |
finalfit Quickly Create Elegant Regression Results Tables and Plots when Modelling | 1.0.4 | 1.0.4 |
FinancialInstrument Financial Instrument Model Infrastructure and Meta-Data | 1.3.1 | 1.3.1 |
FinancialMath Financial Mathematics for Actuaries | 0.1.1 | 0.1.1 |
FinAsym Classifies implicit trading activity from market quotes and<U+000a>computes the probability of informed trading | 1.0 | 1.0 |
fingerprint Functions to Operate on Binary Fingerprint Data | 3.5.7 | 3.5.7 |
finreportr Financial Data from U.S. Securities and Exchange Commission | 1.0.4 | 1.0.4 |
FinTS Companion to Tsay (2005) Analysis of Financial Time Series | 0.4-6 | 0.4-6 |
FisherEM The FisherEM Algorithm to Simultaneously Cluster and Visualize High-Dimensional Data | 1.6 | 1.6 |
fishmethods Fishery Science Methods and Models | 1.11-3 | 1.11-3 |
fishmove Prediction of Fish Movement Parameters | 0.3-3 | 0.3-3 |
fit.models Compare Fitted Models | 0.64 | 0.64 |
FitAR Subset AR Model Fitting | 1.94 | 1.94 |
FitARMA Fit ARMA or ARIMA Using Fast MLE Algorithm | 1.6.1 | 1.6.1 |
fitbitScraper Scrapes Data from Fitbit | 0.1.8 | 0.1.8 |
fitdistrplus Help to Fit of a Parametric Distribution to Non-Censored or Censored Data | 1.1-8 | 1.1-8 |
FITSio FITS (Flexible Image Transport System) Utilities | 2.1-6 | 2.1-6 |
fitteR Fit Hundreds of Theoretical Distributions to Empirical Data | 0.2.0 | 0.2.0 |
FixedPoint Algorithms for Finding Fixed Point Vectors of Functions | 0.6.3 | 0.6.3 |
fixest Fast Fixed-Effects Estimations | 0.10.4 | 0.10.4 |
FKF Fast Kalman Filter | 0.2.4 | 0.2.4 |
flacco Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems | 1.8 | 1.8 |
flars Functional LARS | 1.0 | 1.0 |
flashClust Implementation of optimal hierarchical clustering | 1.01-2 | 1.01-2 |
flexclust Flexible Cluster Algorithms | 1.4-1 | 1.4-1 |
flexdashboard R Markdown Format for Flexible Dashboards | 0.5.2 | 0.5.2 |
FlexDir Tools to Work with the Flexible Dirichlet Distribution | 1.0 | 1.0 |
flexmix Flexible Mixture Modeling | 2.3-19 | 2.3-19 |
flexrsurv Flexible Relative Survival Analysis | 2.0.13 | 2.0.13 |
flexsurv Flexible Parametric Survival and Multi-State Models | 2.2.2 | 2.2.2 |
flextable Functions for Tabular Reporting | 0.7.0 | 0.7.0 |
FLightR Reconstruct Animal Paths from Solar Geolocation Loggers Data | 0.5.2 | 0.5.2 |
float 32-Bit Floats | 0.3-1 | 0.3-1 |
flock Process Synchronization Using File Locks | 0.7 | 0.7 |
flowr Streamlining Design and Deployment of Complex Workflows | 0.9.11 | 0.9.11 |
FlowScreen Daily Streamflow Trend and Change Point Screening | 1.2.6 | 1.2.6 |
flsa Path Algorithm for the General Fused Lasso Signal Approximator | 1.5.2 | 1.5.2 |
FLSSS Mining Rigs for Problems in the Subset Sum Family | 9.1.1 | 9.1.1 |
fma Data Sets from "Forecasting: Methods and Applications" by Makridakis, Wheelwright & Hyndman (1998) | 2.5 | 2.5 |
fmdates Financial Market Date Calculations | 0.1.4 | 0.1.4 |
FME A Flexible Modelling Environment for Inverse Modelling, Sensitivity, Identifiability and Monte Carlo Analysis | 1.3.6.2 | 1.3.6.2 |
fmri Analysis of fMRI Experiments | 1.9.11 | 1.9.11 |
FMStable Finite Moment Stable Distributions | 0.1-4 | 0.1-4 |
fMultivar Rmetrics - Modeling of Multivariate Financial Return Distributions | 3042.80.2 | 3042.80.2 |
FNN Fast Nearest Neighbor Search Algorithms and Applications | 1.1.3.2 | 1.1.3.2 |
fNonlinear Rmetrics - Nonlinear and Chaotic Time Series Modelling | 4021.81 | 4021.81 |
foghorn Summarize CRAN Check Results in the Terminal | 1.4.2 | 1.4.2 |
foieGras Fit Continuous-Time State-Space and Latent Variable Models for Quality Control of Argos Satellite (and Other) Telemetry Data and for Estimating Movement Behaviour | 0.6-9 | 0.6-9 |
fontawesome Easily Work with 'Font Awesome' Icons | 0.5.0 | 0.5.0 |
fontBitstreamVera Fonts with 'Bitstream Vera Fonts' License | 0.1.1 | 0.1.1 |
fontLiberation Liberation Fonts | 0.1.0 | 0.1.0 |
fontquiver Set of Installed Fonts | 0.2.1 | 0.2.1 |
fOptions Rmetrics - Pricing and Evaluating Basic Options | 3042.86 | 3042.86 |
forcats Tools for Working with Categorical Variables (Factors) | 1.0.0 | 1.0.0 |
foreach Provides Foreach Looping Construct | 1.5.2 | 1.5.2 |
ForeCA Forecastable Component Analysis | 0.2.7 | 0.2.7 |
forecast Forecasting Functions for Time Series and Linear Models | 8.21 | 8.21 |
ForecastComb Forecast Combination Methods | 1.3.1 | 1.3.1 |
ForecastCombinations Forecast Combinations | 1.1 | 1.1 |
forecastHybrid Convenient Functions for Ensemble Time Series Forecasts | 5.0.19 | 5.0.19 |
forecastML Time Series Forecasting with Machine Learning Methods | 0.9.0 | 0.9.0 |
forecTheta Forecasting Time Series by Theta Models | 2.6.2 | 2.6.2 |
foreign Read Data Stored by 'Minitab', 'S', 'SAS', 'SPSS', 'Stata', 'Systat', 'Weka', 'dBase', ... | 0.8-82 | 0.8-82 |
forestError A Unified Framework for Random Forest Prediction Error Estimation | 1.1.0 | 1.1.0 |
forestmodel Forest Plots from Regression Models | 0.6.2 | 0.6.2 |
forestplot Advanced Forest Plot Using 'grid' Graphics | 3.1.0 | 3.1.0 |
forge Casting Values into Shape | 0.2.0 | 0.2.0 |
ForImp Imputation of Missing Values Through a Forward Imputation Algorithm | 1.0.3 | 1.0.3 |
formatR Format R Code Automatically | 1.14 | 1.14 |
formattable Create 'Formattable' Data Structures | 0.2.1 | 0.2.1 |
Formula Extended Model Formulas | 1.2-5 | 1.2-5 |
formula.tools Programmatic Utilities for Manipulating Formulas, Expressions, Calls, Assignments and Other R Objects | 1.7.1 | 1.7.1 |
fortunes R Fortunes | 1.5-4 | 1.5-4 |
forward Robust Analysis using Forward Search | 1.0.5 | 1.0.5 |
fourierin Computes Numeric Fourier Integrals | 0.2.4 | 0.2.4 |
fourPNO Bayesian 4 Parameter Item Response Model | 1.1.0 | 1.1.0 |
fpc Flexible Procedures for Clustering | 2.2-9 | 2.2-9 |
fpca Restricted MLE for Functional Principal Components Analysis | 0.2-1 | 0.2-1 |
fPortfolio Rmetrics - Portfolio Selection and Optimization | 3042.83.1 | 3042.83.1 |
fpow Computing the noncentrality parameter of the noncentral F distribution | 0.0-2 | 0.0-2 |
fpp2 Data for "Forecasting: Principles and Practice" (2nd Edition) | 2.5 | 2.5 |
fpp3 Data for "Forecasting: Principles and Practice" (3rd Edition) | 0.5 | 0.5 |
fracdiff Fractionally Differenced ARIMA aka ARFIMA(P,d,q) Models | 1.5-2 | 1.5-2 |
fractal A Fractal Time Series Modeling and Analysis Package | 2.0-4 | 2.0-4 |
frailtyEM Fitting Frailty Models with the EM Algorithm | 1.0.1 | 1.0.1 |
frailtypack Shared, Joint (Generalized) Frailty Models; Surrogate Endpoints | 3.5.0 | 3.5.0 |
Frames2 Estimation in Dual Frame Surveys | 0.2.1 | 0.2.1 |
FRAPO Financial Risk Modelling and Portfolio Optimisation with R | 0.4-1 | 0.4-1 |
frbs Fuzzy Rule-Based Systems for Classification and Regression Tasks | 3.2-0 | 3.2-0 |
fredr An R Client for the 'FRED' API | 2.1.0 | 2.1.0 |
freealg The Free Algebra | 1.1-0 | 1.1-0 |
freegroup The Free Group | 1.1-6 | 1.1-6 |
freetypeharfbuzz Deterministic Computation of Text Box Metrics | 0.2.5 | 0.2.5 |
fRegression Rmetrics - Regression Based Decision and Prediction | 4021.83 | 4021.83 |
freqdom Frequency Domain Based Analysis: Dynamic PCA | 2.0.3 | 2.0.3 |
freqdom.fda Functional Time Series: Dynamic Functional Principal Components | 1.0.1 | 1.0.1 |
freqparcoord Novel Methods for Parallel Coordinates | 1.0.1 | 1.0.1 |
fresh Create Custom 'Bootstrap' Themes to Use in 'Shiny' | 0.2.0 | 0.2.0 |
FrF2 Fractional Factorial Designs with 2-Level Factors | 2.2-3 | 2.2-3 |
FRK Fixed Rank Kriging | 2.1.5 | 2.1.5 |
frm Regression Analysis of Fractional Responses | 1.2.2 | 1.2.2 |
frmqa The Generalized Hyperbolic Distribution, Related Distributions and Their Applications in Finance | 0.1-5 | 0.1-5 |
fromo Fast Robust Moments | 0.2.1 | 0.2.1 |
frontier Stochastic Frontier Analysis | 1.1-8 | 1.1-8 |
fs Cross-Platform File System Operations Based on 'libuv' | 1.6.1 | 1.6.1 |
fslr Wrapper Functions for 'FSL' ('FMRIB' Software Library) from Functional MRI of the Brain ('FMRIB') | 2.25.2 | 2.25.2 |
FSMUMI Imputation of Time Series Based on Fuzzy Logic | 1.0 | 1.0 |
fso Fuzzy Set Ordination | 2.1-2 | 2.1-2 |
fst Lightning Fast Serialization of Data Frames | 0.9.8 | 0.9.8 |
fstcore R Bindings to the 'Fstlib' Library | 0.9.14 | 0.9.14 |
FTICRMS Programs for Analyzing Fourier Transform-Ion Cyclotron Resonance Mass Spectrometry Data | 0.8 | 0.8 |
fts R Interface to 'tslib' (a Time Series Library in C++) | 0.9.9.2 | 0.9.9.2 |
ftsa Functional Time Series Analysis | 6.1 | 6.1 |
ftsspec Spectral Density Estimation and Comparison for Functional Time Series | 1.0.0 | 1.0.0 |
FunCluster Functional Profiling of Microarray Expression Data | 1.09 | 1.09 |
functional Curry, Compose, and other higher-order functions | 0.6 | 0.6 |
funData An S4 Class for Functional Data | 1.3-8 | 1.3-8 |
funFEM Clustering in the Discriminative Functional Subspace | 1.2 | 1.2 |
funHDDC Univariate and Multivariate Model-Based Clustering in Group-Specific Functional Subspaces | 2.3.1 | 2.3.1 |
funLBM Model-Based Co-Clustering of Functional Data | 2.3 | 2.3 |
funtimes Functions for Time Series Analysis | 8.2 | 8.2 |
furrr Apply Mapping Functions in Parallel using Futures | 0.3.1 | 0.3.1 |
futile.logger A Logging Utility for R | 1.4.3 | 1.4.3 |
futile.options Futile Options Management | 1.0.1 | 1.0.1 |
future Unified Parallel and Distributed Processing in R for Everyone | 1.32.0 | 1.32.0 |
future.apply Apply Function to Elements in Parallel using Futures | 1.10.0 | 1.10.0 |
future.BatchJobs A Future API for Parallel and Distributed Processing using BatchJobs | 0.17.0 | 0.17.0 |
future.batchtools A Future API for Parallel and Distributed Processing using 'batchtools' | 0.10.0 | 0.10.0 |
FuzzyR Fuzzy Logic Toolkit for R | 2.3.2 | 2.3.2 |
fuzzyreg Fuzzy Linear Regression | 0.6 | 0.6 |
fxregime Exchange Rate Regime Analysis | 1.0-4 | 1.0-4 |
g.data Delayed-Data Packages | 2.4 | 2.4 |
GA Genetic Algorithms | 3.2.3 | 3.2.3 |
gam Generalized Additive Models | 1.20.1 | 1.20.1 |
gamair Data for 'GAMs: An Introduction with R' | 1.0-2 | 1.0-2 |
gambin Fit the Gambin Model to Species Abundance Distributions | 2.5.0 | 2.5.0 |
GAMBoost Generalized linear and additive models by likelihood based<U+000a>boosting | 1.2-3 | 1.2-3 |
gamboostLSS Boosting Methods for 'GAMLSS' | 2.0-7 | 2.0-7 |
gamboostMSM Boosting Multistate Models | 1.1.88 | 1.1.88 |
gamlr Gamma Lasso Regression | 1.13-7 | 1.13-7 |
gamlss Generalised Additive Models for Location Scale and Shape | 5.4-12 | 5.4-12 |
gamlss.cens Fitting an Interval Response Variable Using `gamlss.family' Distributions | 5.0-1 | 5.0-1 |
gamlss.data Data for Generalised Additive Models for Location Scale and Shape | 6.0-2 | 6.0-2 |
gamlss.dist Distributions for Generalized Additive Models for Location Scale and Shape | 6.0-3 | 6.0-3 |
gamlss.mx Fitting Mixture Distributions with GAMLSS | 6.0-0 | 6.0-0 |
gamm4 Generalized Additive Mixed Models using 'mgcv' and 'lme4' | 0.2-6 | 0.2-6 |
ganalytics Interact with 'Google Analytics' | 0.10.7 | 0.10.7 |
gap Genetic Analysis Package | 1.5-1 | 1.5-1 |
gap.datasets Datasets for 'gap' | 0.0.5 | 0.0.5 |
gapfill Fill Missing Values in Satellite Data | 0.9.6-1 | 0.9.6-1 |
gargle Utilities for Working with Google APIs | 1.3.0 | 1.3.0 |
gaston Genetic Data Handling (QC, GRM, LD, PCA) & Linear Mixed Models | 1.5.7 | 1.5.7 |
gaussDiff Difference measures for multivariate Gaussian probability density functions | 1.1 | 1.1 |
gaussquad Collection of Functions for Gaussian Quadrature | 1.0-3 | 1.0-3 |
gazepath Parse Eye-Tracking Data into Fixations | 1.3 | 1.3 |
gb Generalize Lambda Distribution and Generalized Bootstrapping | 2.3.3 | 2.3.3 |
GB2 Generalized Beta Distribution of the Second Kind: Properties, Likelihood, Estimation | 2.1.1 | 2.1.1 |
gbm Generalized Boosted Regression Models | 2.1.8.1 | 2.1.8.1 |
gbutils Utilities for Simulation, Plots, Quantile Functions and Programming | 0.5 | 0.5 |
gcbd 'GPU'/CPU Benchmarking in Debian-Based Systems | 0.2.6 | 0.2.6 |
gcerisk Generalized Competing Event Model | 19.05.24 | 19.05.24 |
gclus Clustering Graphics | 1.3.2 | 1.3.2 |
GCPM Generalized Credit Portfolio Model | 1.2.2 | 1.2.2 |
gcrma | 2.68.0 | 2.68.0 |
gdalUtilities Wrappers for 'GDAL' Utilities Executables | 1.2.3 | 1.2.3 |
gdalUtils Wrappers for the Geospatial Data Abstraction Library (GDAL) Utilities | 2.0.3.2 | 2.0.3.2 |
gdata Various R Programming Tools for Data Manipulation | 2.18.0.1 | 2.18.0.1 |
gdimap Generalized Diffusion Magnetic Resonance Imaging | 0.1-9 | 0.1-9 |
GDINA The Generalized DINA Model Framework | 2.9.3 | 2.9.3 |
gdistance Distances and Routes on Geographical Grids | 1.6 | 1.6 |
gdns Tools to Work with Google's 'DNS'-over-'HTTPS' ('DoH') API | 0.5.0 | 0.5.0 |
gdpc Generalized Dynamic Principal Components | 1.1.2 | 1.1.2 |
gdtools Utilities for Graphical Rendering and Fonts Management | 0.3.2 | 0.3.2 |
gee Generalized Estimation Equation Solver | 4.13-25 | 4.13-25 |
geeM Solve Generalized Estimating Equations | 0.10.1 | 0.10.1 |
geepack Generalized Estimating Equation Package | 1.3.9 | 1.3.9 |
geigen Calculate Generalized Eigenvalues, the Generalized Schur Decomposition and the Generalized Singular Value Decomposition of a Matrix Pair with Lapack | 2.3 | 2.3 |
geiger Analysis of Evolutionary Diversification | 2.0.10 | 2.0.10 |
gemtc Network Meta-Analysis Using Bayesian Methods | 1.0-1 | 1.0-1 |
genalg R Based Genetic Algorithm | 0.2.1 | 0.2.1 |
GenBinomApps Clopper-Pearson Confidence Interval and Generalized Binomial Distribution | 1.2 | 1.2 |
gender Predict Gender from Names Using Historical Data | 0.6.0 | 0.6.0 |
gendist Generated Probability Distribution Models | 2.0 | 2.0 |
GENEAread Package for Reading Binary Files | 2.0.9 | 2.0.9 |
genefilter | 1.78.0 | 1.78.0 |
GeneNet Modeling and Inferring Gene Networks | 1.2.16 | 1.2.16 |
geneplotter | 1.74.0 | 1.74.0 |
GeneralizedHyperbolic The Generalized Hyperbolic Distribution | 0.8-4 | 0.8-4 |
GeneralizedUmatrix Credible Visualization for Two-Dimensional Projections of Data | 1.2.5 | 1.2.5 |
generics Common S3 Generics not Provided by Base R Methods Related to Model Fitting | 0.1.3 | 0.1.3 |
genesysr Genesys PGR Client | 1.0.0 | 1.0.0 |
genetics Population Genetics | 1.3.8.1.3 | 1.3.8.1.3 |
GenForImp The Forward Imputation: A Sequential Distance-Based Approach for Imputing Missing Data | 1.0 | 1.0 |
genie Fast, Robust, and Outlier Resistant Hierarchical Clustering | 1.0.5 | 1.0.5 |
genieclust Fast and Robust Hierarchical Clustering with Noise Points Detection | 1.1.3 | 1.1.3 |
GenKern Functions for generating and manipulating binned kernel density<U+000a>estimates | 1.2-60 | 1.2-60 |
genlasso Path Algorithm for Generalized Lasso Problems | 1.5 | 1.5 |
GENMETA Implements Generalized Meta-Analysis Using Iterated Reweighted Least Squares Algorithm | 0.2.0 | 0.2.0 |
GenomeInfoDb | 1.32.1 | 1.32.1 |
GenomeInfoDbData | 1.2.8 | 1.2.8 |
GenomicAlignments | 1.32.0 | 1.32.0 |
GenomicFeatures | 1.48.0 | 1.48.0 |
GenomicRanges | 1.48.0 | 1.48.0 |
GenOrd Simulation of Discrete Random Variables with Given Correlation Matrix and Marginal Distributions | 1.4.0 | 1.4.0 |
GenSA R Functions for Generalized Simulated Annealing | 1.1.8 | 1.1.8 |
genSurv Generating Multi-State Survival Data | 1.0.4 | 1.0.4 |
geoaxe Split 'Geospatial' Objects into Pieces | 0.1.0 | 0.1.0 |
geodist Fast, Dependency-Free Geodesic Distance Calculations | 0.0.8 | 0.0.8 |
geofd Spatial Prediction for Function Value Data | 2.0 | 2.0 |
geogrid Turn Geospatial Polygons into Regular or Hexagonal Grids | 0.1.1 | 0.1.1 |
geojson Classes for 'GeoJSON' | 0.3.4 | 0.3.4 |
geojsonio Convert Data from and to 'GeoJSON' or 'TopoJSON' | 0.9.4 | 0.9.4 |
geojsonlint Tools for Validating 'GeoJSON' | 0.4.0 | 0.4.0 |
geojsonsf GeoJSON to Simple Feature Converter | 2.0.2 | 2.0.2 |
geoknife Web-Processing of Large Gridded Datasets | 1.6.10 | 1.6.10 |
GeoLight Analysis of Light Based Geolocator Data | 2.0.0 | 2.0.0 |
GEOmap Topographic and Geologic Mapping | 2.5-0 | 2.5-0 |
geomapdata Data for Topographic and Geologic Mapping | 2.0-0 | 2.0-0 |
GeomComb (Geometric) Forecast Combination Methods | 1.0 | 1.0 |
geometa Tools for Reading and Writing ISO/OGC Geographic Metadata | 0.6-6 | 0.6-6 |
GEOmetadb | 1.58.0 | 1.58.0 |
geometries Convert Between R Objects and Geometric Structures | 0.2.2 | 0.2.2 |
geometry Mesh Generation and Surface Tessellation | 0.4.7 | 0.4.7 |
geomorph Geometric Morphometric Analyses of 2D and 3D Landmark Data | 4.0.3 | 4.0.3 |
geonames Interface to the "Geonames" Spatial Query Web Service | 0.999 | 0.999 |
geonapi 'GeoNetwork' API R Interface | 0.5-3 | 0.5-3 |
GEOquery | 2.64.0 | 2.64.0 |
geoR Analysis of Geostatistical Data | 1.9-2 | 1.9-2 |
georob Robust Geostatistical Analysis of Spatial Data | 0.3-14 | 0.3-14 |
geosapi GeoServer REST API R Interface | 0.5-1 | 0.5-1 |
geoscale Geological Time Scale Plotting | 2.0.1 | 2.0.1 |
geosphere Spherical Trigonometry | 1.5-18 | 1.5-18 |
geospt Geostatistical Analysis and Design of Optimal Spatial Sampling Networks | 1.0-2 | 1.0-2 |
geostatsp Geostatistical Modelling with Likelihood and Bayes | 1.8.2 | 1.8.2 |
geotopbricks An R Plug-in for the Distributed Hydrological Model GEOtop | 1.5.4 | 1.5.4 |
geozoo Zoo of Geometric Objects | 0.5.1 | 0.5.1 |
gepaf Google Encoded Polyline Algorithm Format | 0.1.1 | 0.1.1 |
gert Simple Git Client for R | 1.9.1 | 1.9.1 |
GetHFData Download and Aggregate High Frequency Trading Data from Bovespa | 1.7 | 1.7 |
getMet Get Meteorological Data for Hydrologic Models | 0.3.2 | 0.3.2 |
getmstatistic Quantifying Systematic Heterogeneity in Meta-Analysis | 0.2.2 | 0.2.2 |
getopt C-Like 'getopt' Behavior | 1.20.3 | 1.20.3 |
getPass Masked User Input | 0.2-2 | 0.2-2 |
gets General-to-Specific (GETS) Modelling and Indicator Saturation Methods | 0.37 | 0.37 |
getTBinR Access and Summarise World Health Organization Tuberculosis Data | 0.7.1 | 0.7.1 |
GetTDData Get Data for Brazilian Bonds (Tesouro Direto) | 1.4.5 | 1.4.5 |
GEVStableGarch ARMA-GARCH/APARCH Models with GEV and Stable Distributions | 1.1 | 1.1 |
gfonts Offline 'Google' Fonts for 'Markdown' and 'Shiny' | 0.2.0 | 0.2.0 |
GGally Extension to 'ggplot2' | 2.1.2 | 2.1.2 |
gganimate A Grammar of Animated Graphics | 1.0.8 | 1.0.8 |
ggdag Analyze and Create Elegant Directed Acyclic Graphs | 0.2.4 | 0.2.4 |
ggdemetra 'ggplot2' Extension for Seasonal and Trading Day Adjustment with 'RJDemetra' | 0.2.2 | 0.2.2 |
ggdendro Create Dendrograms and Tree Diagrams Using 'ggplot2' | 0.1.23 | 0.1.23 |
ggdist Visualizations of Distributions and Uncertainty | 3.2.1 | 3.2.1 |
ggeffects Create Tidy Data Frames of Marginal Effects for 'ggplot' from Model Outputs | 1.1.2 | 1.1.2 |
ggExtra Add Marginal Histograms to 'ggplot2', and More 'ggplot2' Enhancements | 0.10.0 | 0.10.0 |
ggfittext Fit Text Inside a Box in 'ggplot2' | 0.9.1 | 0.9.1 |
ggforce Accelerating 'ggplot2' | 0.4.1 | 0.4.1 |
ggformula Formula Interface to the Grammar of Graphics | 0.10.2 | 0.10.2 |
ggfortify Data Visualization Tools for Statistical Analysis Results | 0.4.14 | 0.4.14 |
gghalves Compose Half-Half Plots Using Your Favourite Geoms | 0.1.4 | 0.1.4 |
GGIR Raw Accelerometer Data Analysis | 2.8-2 | 2.8-2 |
ggiraph Make 'ggplot2' Graphics Interactive | 0.8.2 | 0.8.2 |
GGIRread Wearable Accelerometer Data File Readers | 0.2.6 | 0.2.6 |
ggm Graphical Markov Models with Mixed Graphs | 2.5 | 2.5 |
ggmap Spatial Visualization with ggplot2 | 3.0.2 | 3.0.2 |
ggmcmc Tools for Analyzing MCMC Simulations from Bayesian Inference | 1.5.1.1 | 1.5.1.1 |
ggmuller Create Muller Plots of Evolutionary Dynamics | 0.5.6 | 0.5.6 |
ggnewscale Multiple Fill and Colour Scales in 'ggplot2' | 0.4.8 | 0.4.8 |
ggplot2 Create Elegant Data Visualisations Using the Grammar of Graphics | 3.4.1 | 3.4.1 |
ggpubr 'ggplot2' Based Publication Ready Plots | 0.6.0 | 0.6.0 |
ggRandomForests Visually Exploring Random Forests | 2.1.0 | 2.1.0 |
ggraph An Implementation of Grammar of Graphics for Graphs and Networks | 2.0.6 | 2.0.6 |
ggrepel Automatically Position Non-Overlapping Text Labels with 'ggplot2' | 0.9.3 | 0.9.3 |
ggridges Ridgeline Plots in 'ggplot2' | 0.5.4 | 0.5.4 |
ggsci Scientific Journal and Sci-Fi Themed Color Palettes for 'ggplot2' | 3.0.0 | 3.0.0 |
ggseas 'stats' for Seasonal Adjustment on the Fly with 'ggplot2' | 0.5.4 | 0.5.4 |
ggsignif Significance Brackets for 'ggplot2' | 0.6.4 | 0.6.4 |
ggsn North Symbols and Scale Bars for Maps Created with 'ggplot2' or 'ggmap' | 0.5.0 | 0.5.0 |
ggspectra Extensions to 'ggplot2' for Radiation Spectra | 0.3.8 | 0.3.8 |
ggstance Horizontal 'ggplot2' Components | 0.3.6 | 0.3.6 |
ggtext Improved Text Rendering Support for 'ggplot2' | 0.1.2 | 0.1.2 |
ggthemes Extra Themes, Scales and Geoms for 'ggplot2' | 4.2.4 | 4.2.4 |
ggTimeSeries Time Series Visualisations Using the Grammar of Graphics | 1.0.2 | 1.0.2 |
ggvis Interactive Grammar of Graphics | 0.4.8 | 0.4.8 |
ggvoronoi Voronoi Diagrams and Heatmaps with 'ggplot2' | 0.8.4 | 0.8.4 |
gh 'GitHub' 'API' | 1.4.0 | 1.4.0 |
ghyp Generalized Hyperbolic Distribution and Its Special Cases | 1.6.3 | 1.6.3 |
Gifi Multivariate Analysis with Optimal Scaling | 0.4-0 | 0.4-0 |
gifski Highest Quality GIF Encoder | 1.6.6-1 | 1.6.6-1 |
GIGrvg Random Variate Generator for the GIG Distribution | 0.7 | 0.7 |
GillespieSSA Gillespie's Stochastic Simulation Algorithm (SSA) | 0.6.2 | 0.6.2 |
gimme Group Iterative Multiple Model Estimation | 0.7-12 | 0.7-12 |
giphyr R Interface to the Giphy API | 0.2.0 | 0.2.0 |
gistr Work with 'GitHub' 'Gists' | 0.9.0 | 0.9.0 |
git2r Provides Access to Git Repositories | 0.30.1 | 0.30.1 |
gitcreds Query 'git' Credentials from 'R' | 0.1.2 | 0.1.2 |
gitlabr Access to the 'Gitlab' API | 2.0.1 | 2.0.1 |
GJRM Generalised Joint Regression Modelling | 0.2-6.1 | 0.2-6.1 |
gk g-and-k and g-and-h Distribution Functions | 0.5.1 | 0.5.1 |
glarma Generalized Linear Autoregressive Moving Average Models | 1.6-0 | 1.6-0 |
glasso Graphical Lasso: Estimation of Gaussian Graphical Models | 1.11 | 1.11 |
glassoFast Fast Graphical LASSO | 1.0 | 1.0 |
gld Estimation and Use of the Generalised (Tukey) Lambda Distribution | 2.6.6 | 2.6.6 |
GLDEX Fitting Single and Mixture of Generalised Lambda Distributions | 2.0.0.9.2 | 2.0.0.9.2 |
glm2 Fitting Generalized Linear Models | 1.2.1 | 1.2.1 |
GLMMadaptive Generalized Linear Mixed Models using Adaptive Gaussian Quadrature | 0.8-5 | 0.8-5 |
glmmfields Generalized Linear Mixed Models with Robust Random Fields for Spatiotemporal Modeling | 0.1.4 | 0.1.4 |
glmmML Generalized Linear Models with Clustering | 1.1.4 | 1.1.4 |
GLMMRR Generalized Linear Mixed Model (GLMM) for Binary Randomized Response Data | 0.5.0 | 0.5.0 |
glmmTMB Generalized Linear Mixed Models using Template Model Builder | 1.1.3 | 1.1.3 |
glmnet Lasso and Elastic-Net Regularized Generalized Linear Models | 4.1-4 | 4.1-4 |
glmpath L1 Regularization Path for Generalized Linear Models and Cox Proportional Hazards Model | 0.98 | 0.98 |
glmx Generalized Linear Models Extended | 0.1-3 | 0.1-3 |
globalboosttest Testing the additional predictive value of high-dimensional data | 1.1-0 | 1.1-0 |
GlobalOptions Generate Functions to Get or Set Global Options | 0.1.2 | 0.1.2 |
globalOptTests Objective functions for benchmarking the performance of global optimization algorithms | 1.1 | 1.1 |
globals Identify Global Objects in R Expressions | 0.16.2 | 0.16.2 |
glogis Fitting and Testing Generalized Logistic Distributions | 1.0-2 | 1.0-2 |
glpkAPI R Interface to C API of GLPK | 1.3.4 | 1.3.4 |
glrt Generalized Logrank Tests for Interval-censored Failure Time Data | 2.0 | 2.0 |
glue Interpreted String Literals | 1.6.2 | 1.6.2 |
gmailr Access the 'Gmail' 'RESTful' API | 1.0.1 | 1.0.1 |
GMCM Fast Estimation of Gaussian Mixture Copula Models | 1.4 | 1.4 |
GMDH Short Term Forecasting via GMDH-Type Neural Network Algorithms | 1.6 | 1.6 |
Gmedian Geometric Median, k-Medians Clustering and Robust Median PCA | 1.2.7 | 1.2.7 |
gmm Generalized Method of Moments and Generalized Empirical Likelihood | 1.7 | 1.7 |
GMMBoost Likelihood-Based Boosting for Generalized Mixed Models | 1.1.3 | 1.1.3 |
gmnl Multinomial Logit Models with Random Parameters | 1.1-3.2 | 1.1-3.2 |
gmodels Various R Programming Tools for Model Fitting | 2.18.1.1 | 2.18.1.1 |
gmp Multiple Precision Arithmetic | 0.7-1 | 0.7-1 |
gmpoly Multivariate Polynomials with Rational Coefficients | 1.1.0 | 1.1.0 |
gmt Interface Between GMT Map-Making Software and R | 2.0.3 | 2.0.3 |
gmvarkit Estimate Gaussian and Student's t Mixture Vector Autoregressive Models | 2.0.6 | 2.0.6 |
GNAR Methods for Fitting Network Time Series Models | 1.1.1 | 1.1.1 |
gnm Generalized Nonlinear Models | 1.1-2 | 1.1-2 |
gnorm Generalized Normal/Exponential Power Distribution | 1.0.0 | 1.0.0 |
GO.db | 3.15.0 | 3.15.0 |
goftest Classical Goodness-of-Fit Tests for Univariate Distributions | 1.2-3 | 1.2-3 |
gogarch Generalized Orthogonal GARCH (GO-GARCH) Models | 0.7-5 | 0.7-5 |
googleAnalyticsR Google Analytics API into R | 1.0.1 | 1.0.1 |
googleAuthR Authenticate and Create Google APIs | 2.0.0 | 2.0.0 |
googleCloudStorageR Interface with Google Cloud Storage API | 0.7.0 | 0.7.0 |
googleComputeEngineR R Interface with Google Compute Engine | 0.3.0 | 0.3.0 |
googledrive An Interface to Google Drive | 2.0.0 | 2.0.0 |
googleLanguageR Call Google's 'Natural Language' API, 'Cloud Translation' API, 'Cloud Speech' API and 'Cloud Text-to-Speech' API | 0.3.0 | 0.3.0 |
googlePolylines Encoding Coordinates into 'Google' Polylines | 0.8.2 | 0.8.2 |
googlesheets Manage Google Spreadsheets from R | 0.3.0 | 0.3.0 |
googlesheets4 Access Google Sheets using the Sheets API V4 | 1.0.1 | 1.0.1 |
googleVis R Interface to Google Charts | 0.7.1 | 0.7.1 |
GORCure Fit Generalized Odds Rate Mixture Cure Model with Interval Censored Data | 2.0 | 2.0 |
gower Gower's Distance | 1.0.0 | 1.0.0 |
GPareto Gaussian Processes for Pareto Front Estimation and Optimization | 1.1.7 | 1.1.7 |
GPArotation Gradient Projection Factor Rotation | 2023.3-1 | 2023.3-1 |
GPCMlasso Differential Item Functioning in Generalized Partial Credit Models | 0.1-6 | 0.1-6 |
GPFDA Gaussian Process for Functional Data Analysis | 3.1.2 | 3.1.2 |
GPfit Gaussian Processes Modeling | 1.0-8 | 1.0-8 |
gplots Various R Programming Tools for Plotting Data | 3.1.3 | 3.1.3 |
gProfileR Interface to the 'g:Profiler' Toolkit | 0.7.0 | 0.7.0 |
gprofiler2 Interface to the 'g:Profiler' Toolset | 0.2.1 | 0.2.1 |
gradDescent Gradient Descent for Regression Tasks | 3.0 | 3.0 |
granova Graphical Analysis of Variance | 2.1 | 2.1 |
graph graph: A package to handle graph data structures | 1.74.0 | 1.74.0 |
graphicalVAR Graphical VAR for Experience Sampling Data | 0.3 | 0.3 |
graphics | 4.2.3 | 4.2.3 |
graphlayouts Additional Layout Algorithms for Network Visualizations | 0.8.4 | 0.8.4 |
graphTweets Visualise Twitter Interactions | 0.5.3 | 0.5.3 |
GrassmannOptim Grassmann Manifold Optimization | 2.0.1 | 2.0.1 |
gravitas Explore Probability Distributions for Bivariate Temporal Granularities | 0.1.3 | 0.1.3 |
gravity Estimation Methods for Gravity Models | 1.0 | 1.0 |
grDevices | 4.2.3 | 4.2.3 |
gregmisc Greg's Miscellaneous Functions | 2.1.5 | 2.1.5 |
GREMLINS Generalized Multipartite Networks | 0.2.1 | 0.2.1 |
greta Simple and Scalable Statistical Modelling in R | 0.4.3 | 0.4.3 |
greybox Toolbox for Model Building and Forecasting | 1.0.7 | 1.0.7 |
grf Generalized Random Forests | 2.2.1 | 2.2.1 |
grid The Grid Graphics Package | 4.2.3 | 4.2.3 |
gridBase Integration of base and grid graphics | 0.4-7 | 0.4-7 |
gridExtra Miscellaneous Functions for "Grid" Graphics | 2.3 | 2.3 |
gridGraphics Redraw Base Graphics Using 'grid' Graphics | 0.5-1 | 0.5-1 |
gridsample Tools for Grid-Based Survey Sampling Design | 0.2.1 | 0.2.1 |
gridSVG Export 'grid' Graphics as SVG | 1.7-4 | 1.7-4 |
gridtext Improved Text Rendering Support for 'Grid' Graphics | 0.1.5 | 0.1.5 |
GriegSmith Uses Grieg-Smith method on 2 dimentional spatial data | 1.0 | 1.0 |
grImport Importing Vector Graphics | 0.9-5 | 0.9-5 |
grImport2 Importing 'SVG' Graphics | 0.2-0 | 0.2-0 |
grnn General regression neural network | 0.1.0 | 0.1.0 |
GroupSeq Group Sequential Design Probabilities - With Graphical User Interface | 1.4.0 | 1.4.0 |
growfunctions Bayesian Non-Parametric Dependent Models for Time-Indexed Functional Data | 0.15 | 0.15 |
grplasso Fitting User-Specified Models with Group Lasso Penalty | 0.4-7 | 0.4-7 |
grpreg Regularization Paths for Regression Models with Grouped Covariates | 3.4.0 | 3.4.0 |
GSA Gene Set Analysis | 1.03.2 | 1.03.2 |
gsarima Two Functions for Generalized SARIMA Time Series Simulation | 0.1-5 | 0.1-5 |
gsbDesign Group Sequential Bayes Design | 1.0-2 | 1.0-2 |
gsDesign Group Sequential Design | 3.2.2 | 3.2.2 |
GSE Robust Estimation in the Presence of Cellwise and Casewise Contamination and Missing Data | 4.2-1 | 4.2-1 |
GSEABase | 1.58.0 | 1.58.0 |
gSEM Semi-Supervised Generalized Structural Equation Modeling | 0.4.3.4 | 0.4.3.4 |
gset Group Sequential Design in Equivalence Studies | 1.1.0 | 1.1.0 |
gsheet Download Google Sheets Using Just the URL | 0.4.5 | 0.4.5 |
gsl Wrapper for the Gnu Scientific Library | 2.1-8 | 2.1-8 |
GSM Gamma Shape Mixture | 1.3.2 | 1.3.2 |
GSODR Global Surface Summary of the Day ('GSOD') Weather Data Client | 3.1.8 | 3.1.8 |
gss General Smoothing Splines | 2.2-4 | 2.2-4 |
GSSE Genotype-Specific Survival Estimation | 0.1 | 0.1 |
gstat Spatial and Spatio-Temporal Geostatistical Modelling, Prediction and Simulation | 2.0-9 | 2.0-9 |
gsubfn Utilities for Strings and Function Arguments | 0.7 | 0.7 |
gsw Gibbs Sea Water Functions | 1.0-6 | 1.0-6 |
gsynth Generalized Synthetic Control Method | 1.2.1 | 1.2.1 |
gt Easily Create Presentation-Ready Display Tables | 0.7.0 | 0.7.0 |
gtable Arrange 'Grobs' in Tables | 0.3.3 | 0.3.3 |
gte Generalized Turnbull's Estimator | 1.2-3 | 1.2-3 |
gtfsio Read and Write General Transit Feed Specification (GTFS) Files | 1.0.0 | 1.0.0 |
gtheory Apply Generalizability Theory with R | 0.1.2 | 0.1.2 |
gtools Various R Programming Tools | 3.9.3 | 3.9.3 |
gtop Game-Theoretically OPtimal (GTOP) Reconciliation Method | 0.2.0 | 0.2.0 |
gtrendsR Perform and Display Google Trends Queries | 1.5.1 | 1.5.1 |
gtsummary Presentation-Ready Data Summary and Analytic Result Tables | 1.6.0 | 1.6.0 |
Guerry Maps, Data and Methods Related to Guerry (1833) "Moral Statistics of France" | 1.7.4 | 1.7.4 |
GUIDE GUI for DErivatives in R | 1.2.7 | 1.2.7 |
gumbel The Gumbel-Hougaard Copula | 1.10-2 | 1.10-2 |
GUniFrac Generalized UniFrac Distances, Distance-Based Multivariate Methods and Feature-Based Univariate Methods for Microbiome Data Analysis | 1.7 | 1.7 |
gutenbergr Download and Process Public Domain Works from Project Gutenberg | 0.2.1 | 0.2.1 |
gWidgets gWidgets API for Building Toolkit-Independent, Interactive GUIs | 0.0-54.2 | 0.0-54.2 |
gWidgets2 Rewrite of gWidgets API for Simplified GUI Construction | 1.0-9 | 1.0-9 |
gWidgets2tcltk Toolkit Implementation of gWidgets2 for tcltk | 1.0-8 | 1.0-8 |
gWidgetsRGtk2 Toolkit Implementation of gWidgets for RGtk2 | 0.0-86.1 | 0.0-86.1 |
GWmodel Geographically-Weighted Models | 2.2-9 | 2.2-9 |
gwrr Fits Geographically Weighted Regression Models with Diagnostic Tools | 0.2-2 | 0.2-2 |
GWSDAT GroundWater Spatiotemporal Data Analysis Tool (GWSDAT) | 3.1.1 | 3.1.1 |
h2o R Interface for the 'H2O' Scalable Machine Learning Platform | 3.36.0.4 | 3.36.0.4 |
HAC Estimation, Simulation and Visualization of Hierarchical Archimedean Copulae (HAC) | 1.1-0 | 1.1-0 |
HadoopStreaming Utilities for using R scripts in Hadoop streaming | 0.2 | 0.2 |
HandTill2001 Multiple Class Area under ROC Curve | 1.0.1 | 1.0.1 |
hapassoc Inference of Trait Associations with SNP Haplotypes and Other Attributes using the EM Algorithm | 1.2-9 | 1.2-9 |
Haplin Analyzing Case-Parent Triad and/or Case-Control Data with SNP Haplotypes | 7.2.3 | 7.2.3 |
haplo.stats Statistical Analysis of Haplotypes with Traits and Covariates when Linkage Phase is Ambiguous | 1.8.7 | 1.8.7 |
HaploSim Functions to Simulate Haplotypes | 1.8.4.2 | 1.8.4.2 |
hardhat Construct Modeling Packages | 1.2.0 | 1.2.0 |
HardyWeinberg Statistical Tests and Graphics for Hardy-Weinberg Equilibrium | 1.7.5 | 1.7.5 |
harmonicmeanp Harmonic Mean p-Values and Model Averaging by Mean Maximum Likelihood | 3.0 | 3.0 |
HarmonicRegression Harmonic Regression to One or more Time Series | 1.0 | 1.0 |
HARtools Read HTTP Archive ('HAR') Data | 0.0.5 | 0.0.5 |
hash Full Featured Implementation of Hash Tables/Associative Arrays/Dictionaries | 2.2.6.2 | 2.2.6.2 |
haven Import and Export 'SPSS', 'Stata' and 'SAS' Files | 2.5.2 | 2.5.2 |
hbsae Hierarchical Bayesian Small Area Estimation | 1.2 | 1.2 |
hda Heteroscedastic Discriminant Analysis | 0.2-14 | 0.2-14 |
HDclassif High Dimensional Supervised Classification and Clustering | 2.2.0 | 2.2.0 |
hddplot Use Known Groups in High-Dimensional Data to Derive Scores for Plots | 0.59 | 0.59 |
hddtools Hydrological Data Discovery Tools | 0.9.4 | 0.9.4 |
hdf5r Interface to the 'HDF5' Binary Data Format | 1.3.5 | 1.3.5 |
hdi High-Dimensional Inference | 0.1-9 | 0.1-9 |
HDInterval Highest (Posterior) Density Intervals | 0.2.4 | 0.2.4 |
hdm High-Dimensional Metrics | 0.3.1 | 0.3.1 |
hdnom Benchmarking and Visualization Toolkit for Penalized Cox Models | 6.0.1 | 6.0.1 |
hdrcde Highest Density Regions and Conditional Density Estimation | 3.4 | 3.4 |
HDtweedie The Lasso for Tweedie's Compound Poisson Model Using an IRLS-BMD Algorithm | 1.1 | 1.1 |
Heatplus | 3.4.0 | 3.4.0 |
hellno Providing 'stringsAsFactors=FALSE' Variants of 'data.frame()' and 'as.data.frame()' | 0.0.1 | 0.0.1 |
heplots Visualizing Hypothesis Tests in Multivariate Linear Models | 1.4-2 | 1.4-2 |
here A Simpler Way to Find Your Files | 1.0.1 | 1.0.1 |
hermite Generalized Hermite Distribution | 1.1.2 | 1.1.2 |
het.test White's Test for Heteroskedasticity | 0.1 | 0.1 |
hexbin Hexagonal Binning Routines | 1.28.3 | 1.28.3 |
hexView Viewing Binary Files | 0.3-4 | 0.3-4 |
HGNChelper Identify and Correct Invalid HGNC Human Gene Symbols and MGI Mouse Gene Symbols | 0.8.1 | 0.8.1 |
hgu133plus2.db | 3.13.0 | 3.13.0 |
hgu133plus2cdf | 2.18.0 | 2.18.0 |
hgu95av2.db | 3.13.0 | 3.13.0 |
hgu95av2cdf | 2.18.0 | 2.18.0 |
HH Statistical Analysis and Data Display: Heiberger and Holland | 3.1-49 | 3.1-49 |
hht The Hilbert-Huang Transform: Tools and Methods | 2.1.6 | 2.1.6 |
HI Simulation from Distributions Supported by Nested Hyperplanes | 0.5 | 0.5 |
HiddenMarkov Hidden Markov Models | 1.8-13 | 1.8-13 |
hierfstat Estimation and Tests of Hierarchical F-Statistics | 0.5-10 | 0.5-10 |
highfrequency Tools for Highfrequency Data Analysis | 1.0.0 | 1.0.0 |
highlight Syntax Highlighter | 0.5.1 | 0.5.1 |
highr Syntax Highlighting for R Source Code | 0.9 | 0.9 |
hipread Read Hierarchical Fixed Width Files | 0.2.3 | 0.2.3 |
HistData Data Sets from the History of Statistics and Data Visualization | 0.8-7 | 0.8-7 |
histogram Construction of Regular and Irregular Histograms with Different Options for Automatic Choice of Bins | 0.0-25 | 0.0-25 |
HistogramTools Utility Functions for R Histograms | 0.3.2 | 0.3.2 |
hitandrun "Hit and Run" and "Shake and Bake" for Sampling Uniformly from Convex Shapes | 0.5-6 | 0.5-6 |
HLMdiag Diagnostic Tools for Hierarchical (Multilevel) Linear Models | 0.5.0 | 0.5.0 |
hmi Hierarchical Multiple Imputation | 1.0.0 | 1.0.0 |
Hmisc Harrell Miscellaneous | 5.0-1 | 5.0-1 |
HMP Hypothesis Testing and Power Calculations for Comparing Metagenomic Samples from HMP | 2.0.1 | 2.0.1 |
HMPTrees Statistical Object Oriented Data Analysis of RDP-Based Taxonomic Trees from Human Microbiome Data | 1.4 | 1.4 |
hms Pretty Time of Day | 1.1.2 | 1.1.2 |
hNMF Hierarchical Non-Negative Matrix Factorization | 1.0 | 1.0 |
hoardr Manage Cached Files | 0.5.3 | 0.5.3 |
homals Gifi Methods for Optimal Scaling | 1.0-10 | 1.0-10 |
homologene Quick Access to Homologene and Gene Annotation Updates | 1.4.68.19.3.27 | 1.4.68.19.3.27 |
hot.deck Multiple Hot Deck Imputation | 1.2 | 1.2 |
hrbrthemes Additional Themes, Theme Components and Utilities for 'ggplot2' | 0.8.0 | 0.8.0 |
HSAUR3 A Handbook of Statistical Analyses Using R (3rd Edition) | 1.0-13 | 1.0-13 |
HSROC Meta-Analysis of Diagnostic Test Accuracy when Reference Test is Imperfect | 2.1.9 | 2.1.9 |
htm2txt Convert Html into Text | 2.2.2 | 2.2.2 |
htmltab Assemble Data Frames from HTML Tables | 0.8.2 | 0.8.2 |
htmlTable Advanced Tables for Markdown/HTML | 2.4.1 | 2.4.1 |
htmltidy Tidy Up and Test XPath Queries on HTML and XML Content | 0.5.0 | 0.5.0 |
htmltools Tools for HTML | 0.5.5 | 0.5.5 |
HTMLUtils Facilitates Automated HTML Report Creation | 0.1.8 | 0.1.8 |
htmlwidgets HTML Widgets for R | 1.6.2 | 1.6.2 |
hts Hierarchical and Grouped Time Series | 6.0.2 | 6.0.2 |
httpcache Query Cache for HTTP Clients | 1.2.0 | 1.2.0 |
httpcode 'HTTP' Status Code Helper | 0.3.0 | 0.3.0 |
httping 'Ping' 'URLs' to Time 'Requests' | 0.2.0 | 0.2.0 |
httpRequest Basic HTTP Request | 0.0.11 | 0.0.11 |
httptest A Test Environment for HTTP Requests | 4.1.0 | 4.1.0 |
httpuv HTTP and WebSocket Server Library | 1.6.9 | 1.6.9 |
httr Tools for Working with URLs and HTTP | 1.4.5 | 1.4.5 |
httr2 Perform HTTP Requests and Process the Responses | 0.2.2 | 0.2.2 |
humanFormat Human-Friendly Formatting Functions | 1.2 | 1.2 |
humidity Calculate Water Vapor Measures from Temperature and Dew Point | 0.1.5 | 0.1.5 |
hunspell High-Performance Stemmer, Tokenizer, and Spell Checker | 3.0.2 | 3.0.2 |
hutils Miscellaneous R Functions and Aliases | 1.8.1 | 1.8.1 |
huxtable Easily Create and Style Tables for LaTeX, HTML and Other Formats | 5.5.2 | 5.5.2 |
hwde Models and Tests for Departure from Hardy-Weinberg Equilibrium and Independence Between Loci | 0.67 | 0.67 |
hwriter HTML Writer - Outputs R Objects in HTML Format | 1.3.2.1 | 1.3.2.1 |
hwwntest Tests of White Noise using Wavelets | 1.3.1 | 1.3.1 |
hydroApps Tools and models for hydrological applications | 0.1-1 | 0.1-1 |
hydrogeo Groundwater Data Presentation and Interpretation | 0.6-1 | 0.6-1 |
hydroGOF Goodness-of-Fit Functions for Comparison of Simulated and Observed Hydrological Time Series | 0.4-0 | 0.4-0 |
hydrolinks Hydrologic Network Linking Data and Tools | 0.10.0 | 0.10.0 |
HydroMe Estimating Water Retention and Infiltration Model Parameters using Experimental Data | 2.0-1 | 2.0-1 |
hydroPSO Particle Swarm Optimisation, with Focus on Environmental Models | 0.5-1 | 0.5-1 |
hydroscoper Interface to the Greek National Data Bank for Hydrometeorological Information | 1.4.1 | 1.4.1 |
hydrostats Hydrologic Indices for Daily Time Series Data | 0.2.9 | 0.2.9 |
hydroTSM Time Series Management, Analysis and Interpolation for Hydrological Modelling | 0.6-0 | 0.6-0 |
hyfo Hydrology and Climate Forecasting | 1.4.3 | 1.4.3 |
hyper2 The Hyperdirichlet Distribution, Mark 2 | 3.0-0 | 3.0-0 |
HyperbolicDist The Hyperbolic Distribution | 0.6-4 | 0.6-4 |
hypergeo The Gauss Hypergeometric Function | 1.2-13 | 1.2-13 |
HypergeoMat Hypergeometric Function of a Matrix Argument | 4.0.2 | 4.0.2 |
HyPhy Macroevolutionary phylogentic analysis of species trees and gene trees | 1.0 | 1.0 |
iai Interface to 'Interpretable AI' Modules | 1.8.0 | 1.8.0 |
ibd Incomplete Block Designs | 1.5 | 1.5 |
ibdreg Regression Methods for IBD Linkage with Covariates | 0.3.8 | 0.3.8 |
ibelief Belief Function Implementation | 1.3.1 | 1.3.1 |
ibmdbR IBM in-Database Analytics for R | 1.50.0 | 1.50.0 |
iBreakDown Model Agnostic Instance Level Variable Attributions | 2.0.1 | 2.0.1 |
IBrokers R API to Interactive Brokers Trader Workstation | 0.10-2 | 0.10-2 |
IC2 Inequality and Concentration Indices and Curves | 1.0-1 | 1.0-1 |
ica Independent Component Analysis | 1.0-3 | 1.0-3 |
icarus Calibrates and Reweights Units in Samples | 0.3.1 | 0.3.1 |
ICBayes Bayesian Semiparametric Models for Interval-Censored Data | 1.2 | 1.2 |
ICC Facilitating Estimation of the Intraclass Correlation Coefficient | 2.4.0 | 2.4.0 |
iccbeta Multilevel Model Intraclass Correlation for Slope Heterogeneity | 1.2.0 | 1.2.0 |
icdGLM EM by the Method of Weights for Incomplete Categorical Data in Generlized Linear Models | 1.0.0 | 1.0.0 |
ICE Iterated Conditional Expectation | 0.69 | 0.69 |
ICEbox Individual Conditional Expectation Plot Toolbox | 1.1.5 | 1.1.5 |
icenReg Regression Models for Interval Censored Data | 2.0.15 | 2.0.15 |
Icens NPMLE for Censored and Truncated Data | 1.68.0 | 1.68.0 |
icensmis Study Design and Data Analysis in the Presence of Error-Prone Diagnostic Tests and Self-Reported Outcomes | 1.5.0 | 1.5.0 |
ICGOR Fit Generalized Odds Rate Hazards Model with Interval Censored Data | 2.0 | 2.0 |
icRSF A Modified Random Survival Forest Algorithm | 1.2 | 1.2 |
ICS Tools for Exploring Multivariate Data via ICS/ICA | 1.3-1 | 1.3-1 |
ICSNP Tools for Multivariate Nonparametrics | 1.1-1 | 1.1-1 |
ICsurv Semiparametric Regression Analysis of Interval-Censored Data | 1.0.1 | 1.0.1 |
idbr R Interface to the US Census Bureau International Data Base API | 1.0 | 1.0 |
IDE Integro-Difference Equation Spatio-Temporal Models | 0.3.1 | 0.3.1 |
idendr0 Interactive Dendrograms | 1.5.3 | 1.5.3 |
IDPmisc 'Utilities of Institute of Data Analyses and Process Design (www.zhaw.ch/idp)' | 1.1.20 | 1.1.20 |
IDPSurvival Imprecise Dirichlet Process for Survival Analysis | 1.2 | 1.2 |
ids Generate Random Identifiers | 1.0.1 | 1.0.1 |
ifaTools Toolkit for Item Factor Analysis with 'OpenMx' | 0.23 | 0.23 |
ifultools Insightful Research Tools | 2.0-23 | 2.0-23 |
igraph Network Analysis and Visualization | 1.4.1 | 1.4.1 |
ihs Inverse Hyperbolic Sine Distribution | 1.0 | 1.0 |
illuminaio | 0.38.0 | 0.38.0 |
imguR An Imgur.com API Client Package | 1.0.3 | 1.0.3 |
IMIFA Infinite Mixtures of Infinite Factor Analysers and Related Models | 2.1.9 | 2.1.9 |
immer Item Response Models for Multiple Ratings | 1.4-15 | 1.4-15 |
impimp Imprecise Imputation for Statistical Matching | 0.3.1 | 0.3.1 |
implyr R Interface for Apache Impala | 0.4.0 | 0.4.0 |
import An Import Mechanism for R | 1.3.0 | 1.3.0 |
impute impute: Imputation for microarray data | 1.70.0 | 1.70.0 |
imputeFin Imputation of Financial Time Series with Missing Values and/or Outliers | 0.1.2 | 0.1.2 |
imputePSF Impute Missing Data in Time Series Data with PSF Based Method | 0.1.0 | 0.1.0 |
imputeR A General Multivariate Imputation Framework | 2.2 | 2.2 |
imputeTestbench Test Bench for the Comparison of Imputation Methods | 3.0.3 | 3.0.3 |
imputeTS Time Series Missing Value Imputation | 3.3 | 3.3 |
imputeYn Imputing the Last Largest Censored Observation(s) Under Weighted Least Squares | 1.3 | 1.3 |
in2extRemes Into the extRemes Package | 1.0-3 | 1.0-3 |
IncDTW Incremental Calculation of Dynamic Time Warping | 1.1.4.4 | 1.1.4.4 |
inegiR Integrate INEGI’s (Mexican Stats Office) API with R | 3.0.0 | 3.0.0 |
ineq Measuring Inequality, Concentration, and Poverty | 0.2-13 | 0.2-13 |
infer Tidy Statistical Inference | 1.0.4 | 1.0.4 |
inflection Finds the Inflection Point of a Curve | 1.3.6 | 1.3.6 |
influence.ME Tools for Detecting Influential Data in Mixed Effects Models | 0.9-9 | 0.9-9 |
influence.SEM Case Influence in Structural Equation Models | 2.3 | 2.3 |
influenceR Software Tools to Quantify Structural Importance of Nodes in a Network | 0.1.0.1 | 0.1.0.1 |
influxdbr R Interface to InfluxDB | 0.14.2 | 0.14.2 |
infotheo Information-Theoretic Measures | 1.2.0.1 | 1.2.0.1 |
InfoTrad Calculates the Probability of Informed Trading (PIN) | 1.2 | 1.2 |
ingredients Effects and Importances of Model Ingredients | 2.3.0 | 2.3.0 |
ini Read and Write '.ini' Files | 0.3.1 | 0.3.1 |
inline Functions to Inline C, C++, Fortran Function Calls from R | 0.3.19 | 0.3.19 |
inlmisc Miscellaneous Functions for the USGS INL Project Office | 0.5.2 | 0.5.2 |
insight Easy Access to Model Information for Various Model Objects | 0.19.1 | 0.19.1 |
InspectChangepoint High-Dimensional Changepoint Estimation via Sparse Projection | 1.2 | 1.2 |
instaR Access to Instagram API via R | 0.2.4 | 0.2.4 |
intamap Procedures for Automated Interpolation | 1.4-16 | 1.4-16 |
intccr Semiparametric Competing Risks Regression under Interval Censoring | 3.0.4 | 3.0.4 |
interactiveDisplayBase | 1.34.0 | 1.34.0 |
internetarchive An API Client for the Internet Archive | 0.1.6 | 0.1.6 |
interp Interpolation Methods | 1.1-3 | 1.1-3 |
Interpol.T Hourly interpolation of multiple temperature daily series | 2.1.1 | 2.1.1 |
interval Weighted Logrank Tests and NPMLE for Interval Censored Data | 1.1-0.8 | 1.1-0.8 |
intervals Tools for Working with Points and Intervals | 0.15.3 | 0.15.3 |
IntervalSurgeon Operating on Integer-Bounded Intervals | 1.1 | 1.1 |
inum Interval and Enum-Type Representation of Vectors | 1.0-5 | 1.0-5 |
investr Inverse Estimation/Calibration Functions | 1.4.2 | 1.4.2 |
invgamma The Inverse Gamma Distribution | 1.1 | 1.1 |
invGauss Threshold Regression that Fits the (Randomized Drift) Inverse Gaussian Distribution to Survival Data | 1.2 | 1.2 |
ipdmeta Tools for subgroup analyses with multiple trial data using aggregate statistics | 2.4 | 2.4 |
ipdw Spatial Interpolation by Inverse Path Distance Weighting | 2.0-0 | 2.0-0 |
iplots iPlots - Interactive Graphics for R | 1.1-7.1 | 1.1-7.1 |
ipred Improved Predictors | 0.9-14 | 0.9-14 |
ips Interfaces to Phylogenetic Software in R | 0.0.11 | 0.0.11 |
iptools Manipulate, Validate and Resolve 'IP' Addresses | 0.7.2 | 0.7.2 |
ipumsr Read 'IPUMS' Extract Files | 0.5.1 | 0.5.1 |
ipw Estimate Inverse Probability Weights | 1.2 | 1.2 |
IPWboxplot Adapted Boxplot to Missing Observations | 0.1.1 | 0.1.1 |
irace Iterated Racing for Automatic Algorithm Configuration | 3.4.1 | 3.4.1 |
IRanges | 2.30.0 | 2.30.0 |
IRdisplay 'Jupyter' Display Machinery | 1.1 | 1.1 |
IRkernel Native R Kernel for the 'Jupyter Notebook' | 1.3 | 1.3 |
irlba Fast Truncated Singular Value Decomposition and Principal Components Analysis for Large Dense and Sparse Matrices | 2.3.5.1 | 2.3.5.1 |
IROmiss Imputation Regularized Optimization Algorithm | 1.0.2 | 1.0.2 |
irr Various Coefficients of Interrater Reliability and Agreement | 0.84.1 | 0.84.1 |
irtDemo Item Response Theory Demo Collection | 0.1.4 | 0.1.4 |
irtoys A Collection of Functions Related to Item Response Theory (IRT) | 0.2.2 | 0.2.2 |
irtProb Utilities and Probability Distributions Related to Multidimensional Person Item Response Models | 1.2 | 1.2 |
irtrees Estimation of Tree-Based Item Response Models | 1.0.0 | 1.0.0 |
IRTShiny Item Response Theory via Shiny | 1.2 | 1.2 |
isdparser Parse 'NOAA' Integrated Surface Data Files | 0.4.0 | 0.4.0 |
IsingFit Fitting Ising Models Using the ELasso Method | 0.3.1 | 0.3.1 |
IsingSampler Sampling Methods and Distribution Functions for the Ising Model | 0.2.1 | 0.2.1 |
ISLR Data for an Introduction to Statistical Learning with Applications in R | 1.4 | 1.4 |
ismev An Introduction to Statistical Modeling of Extreme Values | 1.42 | 1.42 |
Iso Functions to Perform Isotonic Regression | 0.0-18.1 | 0.0-18.1 |
isoband Generate Isolines and Isobands from Regularly Spaced Elevation Grids | 0.2.6 | 0.2.6 |
ISOcodes Selected ISO Codes | 2022.09.29 | 2022.09.29 |
isopam Clustering of Sites with Species Data | 0.9-13 | 0.9-13 |
IsoSpecR The IsoSpec Algorithm | 2.1.3 | 2.1.3 |
isotone Active Set and Generalized PAVA for Isotone Optimization | 1.1-1 | 1.1-1 |
isotree Isolation-Based Outlier Detection | 0.5.19-1 | 0.5.19-1 |
ISOweek Week of the year and weekday according to ISO 8601 | 0.6-2 | 0.6-2 |
ISwR Introductory Statistics with R | 2.0-8 | 2.0-8 |
iteRates Parametric rate comparison | 3.1 | 3.1 |
iterators Provides Iterator Construct | 1.0.14 | 1.0.14 |
iterLap Approximate Probability Densities by Iterated Laplace Approximations | 1.1-3 | 1.1-3 |
iterpc Efficient Iterator for Permutations and Combinations | 0.4.2 | 0.4.2 |
itertools Iterator Tools | 0.1-3 | 0.1-3 |
itsmr Time Series Analysis Using the Innovations Algorithm | 1.10 | 1.10 |
ivfixed Instrumental fixed effect panel data model | 1.0 | 1.0 |
ivpack Instrumental Variable Estimation. | 1.2 | 1.2 |
ivpanel Instrumental Panel Data Models | 1.0 | 1.0 |
ivprobit Instrumental Variables Probit Model | 1.1 | 1.1 |
jaatha Simulation-Based Maximum Likelihood Parameter Estimation | 3.2.2 | 3.2.2 |
jack Jack, Zonal, and Schur Polynomials | 3.0.0 | 3.0.0 |
jackknifeKME Jackknife Estimates of Kaplan-Meier Estimators or Integrals | 1.2 | 1.2 |
JADE Blind Source Separation Methods Based on Joint Diagonalization and Some BSS Performance Criteria | 2.0-3 | 2.0-3 |
janeaustenr Jane Austen's Complete Novels | 1.0.0 | 1.0.0 |
janitor Simple Tools for Examining and Cleaning Dirty Data | 2.2.0 | 2.2.0 |
jarbes Just a Rather Bayesian Evidence Synthesis | 2.0.0 | 2.0.0 |
JavaGD Java Graphics Device | 0.6-5 | 0.6-5 |
Jaya Jaya, a Gradient-Free Optimization Algorithm | 0.1.9 | 0.1.9 |
JBTools Misc Small Tools and Helper Functions for Other Code of J. Buttlar | 0.7.2.9 | 0.7.2.9 |
JM Joint Modeling of Longitudinal and Survival Data | 1.5-2 | 1.5-2 |
Jmisc Julian Miscellaneous Function | 0.3.1.1 | 0.3.1.1 |
jmvcore Dependencies for the 'jamovi' Framework | 2.3.19 | 2.3.19 |
joineR Joint Modelling of Repeated Measurements and Time-to-Event Data | 1.2.8 | 1.2.8 |
joineRmeta Joint Modelling for Meta-Analytic (Multi-Study) Data | 0.1.2 | 0.1.2 |
joint.Cox Joint Frailty-Copula Models for Tumour Progression and Death in Meta-Analysis | 3.16 | 3.16 |
JointAI Joint Analysis and Imputation of Incomplete Data | 1.0.4 | 1.0.4 |
JointModel Semiparametric Joint Models for Longitudinal and Counting Processes | 1.0 | 1.0 |
jomo Multilevel Joint Modelling Multiple Imputation | 2.7-4 | 2.7-4 |
JoSAE Unit-Level and Area-Level Small Area Estimation | 0.3.0 | 0.3.0 |
jose JavaScript Object Signing and Encryption | 1.2.0 | 1.2.0 |
jpeg Read and write JPEG images | 0.1-9 | 0.1-9 |
jqr Client for 'jq', a 'JSON' Processor | 1.2.3 | 1.2.3 |
jquerylib Obtain 'jQuery' as an HTML Dependency Object | 0.1.4 | 0.1.4 |
jrc Exchange Commands Between R and 'JavaScript' | 0.5.1 | 0.5.1 |
jrt Item Response Theory Modeling and Scoring for Judgment Data | 1.1.1 | 1.1.1 |
jsonify Convert Between 'R' Objects and Javascript Object Notation (JSON) | 1.2.2 | 1.2.2 |
jsonld JSON for Linking Data | 2.2 | 2.2 |
jsonlite A Simple and Robust JSON Parser and Generator for R | 1.8.3 | 1.8.3 |
jsonvalidate Validate 'JSON' Schema | 1.3.2 | 1.3.2 |
jstor Read Data from JSTOR/DfR | 0.3.10 | 0.3.10 |
jtools Analysis and Presentation of Social Scientific Data | 2.1.4 | 2.1.4 |
JuliaCall Seamless Integration Between R and 'Julia' | 0.17.5 | 0.17.5 |
JuliaConnectoR A Functionally Oriented Interface for Integrating 'Julia' with R | 1.1.1 | 1.1.1 |
kableExtra Construct Complex Table with 'kable' and Pipe Syntax | 1.3.4 | 1.3.4 |
kaps K-Adaptive Partitioning for Survival data | 1.0.2 | 1.0.2 |
katex Rendering Math to HTML, 'MathML', or R-Documentation Format | 1.4.0 | 1.4.0 |
kcirt k-Cube Thurstonian IRT Models | 0.6.0 | 0.6.0 |
kdetrees Nonparametric method for identifying discordant phylogenetic trees | 0.1.5 | 0.1.5 |
kdist K-Distribution and Weibull Paper | 0.2 | 0.2 |
kedd Kernel Estimator and Bandwidth Selection for Density and Its Derivatives | 1.0.3 | 1.0.3 |
keep Arrays with Better Control over Dimension Dropping | 1.0 | 1.0 |
KEGGREST | 1.36.0 | 1.36.0 |
kelvin Calculate Solutions to the Kelvin Differential Equation using Bessel Functions | 2.0-2 | 2.0-2 |
Kendall Kendall Rank Correlation and Mann-Kendall Trend Test | 2.2.1 | 2.2.1 |
kendallRandomWalks Simulate and Visualize Kendall Random Walks and Related Distributions | 0.9.4 | 0.9.4 |
KenSyn Knowledge Synthesis in Agriculture - From Experimental Network to Meta-Analysis | 0.3 | 0.3 |
kequate The Kernel Method of Test Equating | 1.6.4 | 1.6.4 |
keras R Interface to 'Keras' | 2.9.0 | 2.9.0 |
kernelboot Smoothed Bootstrap and Random Generation from Kernel Densities | 0.1.9 | 0.1.9 |
kernlab Kernel-Based Machine Learning Lab | 0.9-32 | 0.9-32 |
KernSmooth Functions for Kernel Smoothing Supporting Wand & Jones (1995) | 2.23-20 | 2.23-20 |
keyring Access the System Credential Store from R | 1.3.0 | 1.3.0 |
KFAS Kalman Filter and Smoother for Exponential Family State Space Models | 1.5.0 | 1.5.0 |
kfigr Integrated Code Chunk Anchoring and Referencing for R Markdown Documents | 1.2.1 | 1.2.1 |
KFKSDS Kalman Filter, Smoother and Disturbance Smoother | 1.6 | 1.6 |
kimisc Kirill's Miscellaneous Functions | 0.4 | 0.4 |
kinship2 Pedigree Functions | 1.9.6 | 1.9.6 |
kitagawa Spectral Response of Water Wells to Harmonic Strain and Pressure Signals | 3.1.0 | 3.1.0 |
kiwisR A Wrapper for Querying KISTERS 'WISKI' Databases via the 'KiWIS' API | 0.2.0 | 0.2.0 |
kknn Weighted k-Nearest Neighbors | 1.3.1 | 1.3.1 |
klaR Classification and Visualization | 1.7-0 | 1.7-0 |
km.ci Confidence Intervals for the Kaplan-Meier Estimator | 0.5-6 | 0.5-6 |
kmc Kaplan-Meier Estimator with Constraints for Right Censored Data -- a Recursive Computational Algorithm | 0.2-4 | 0.2-4 |
kmconfband Kaplan-Meier Simultaneous Confidence Band for the Survivor Function | 0.1 | 0.1 |
kmer Fast K-Mer Counting and Clustering for Biological Sequence Analysis | 1.1.2 | 1.1.2 |
kmi Kaplan-Meier Multiple Imputation for the Analysis of Cumulative Incidence Functions in the Competing Risks Setting | 0.5.5 | 0.5.5 |
kml K-Means for Longitudinal Data | 2.4.6 | 2.4.6 |
KMsurv Data sets from Klein and Moeschberger (1997), Survival Analysis | 0.1-5 | 0.1-5 |
knitcitations Citations for 'Knitr' Markdown Files | 1.0.12 | 1.0.12 |
knitLatex 'Knitr' Helpers - Mostly Tables | 0.9.0 | 0.9.0 |
knitr A General-Purpose Package for Dynamic Report Generation in R | 1.42 | 1.42 |
kofnGA A Genetic Algorithm for Fixed-Size Subset Selection | 1.3 | 1.3 |
kohonen Supervised and Unsupervised Self-Organising Maps | 3.0.11 | 3.0.11 |
kolmim An Improved Evaluation of Kolmogorov's Distribution | 1.0 | 1.0 |
koRpus Text Analysis with Emphasis on POS Tagging, Readability, and Lexical Diversity | 0.13-8 | 0.13-8 |
KrigInv Kriging-Based Inversion for Deterministic and Noisy Computer Experiments | 1.4.2 | 1.4.2 |
ks Kernel Smoothing | 1.14.0 | 1.14.0 |
kSamples K-Sample Rank Tests and their Combinations | 1.2-9 | 1.2-9 |
KScorrect Lilliefors-Corrected Kolmogorov-Smirnov Goodness-of-Fit Tests | 1.4.0 | 1.4.0 |
kst Knowledge Space Theory | 0.5-4 | 0.5-4 |
ktsolve Configurable Function for Solving Families of Nonlinear Equations | 1.3 | 1.3 |
kubik Cubic Hermite Splines and Related Root Finding Methods | 0.3.0 | 0.3.0 |
kutils Project Management Tools | 1.70 | 1.70 |
kwb.hantush Calculation of Groundwater Mounding Beneath an Infiltration Basin | 0.3.0 | 0.3.0 |
kyotil Utility Functions for Statistical Analysis Report Generation and Monte Carlo Studies | 2023.2-2 | 2023.2-2 |
kza Kolmogorov-Zurbenko Adaptive Filters | 4.1.0.1 | 4.1.0.1 |
L0Learn Fast Algorithms for Best Subset Selection | 2.0.3 | 2.0.3 |
labdsv Ordination and Multivariate Analysis for Ecology | 2.0-1 | 2.0-1 |
label.switching Relabelling MCMC Outputs of Mixture Models | 1.8 | 1.8 |
labeling Axis Labeling | 0.4.2 | 0.4.2 |
labelled Manipulating Labelled Data | 2.10.0 | 2.10.0 |
labelVector Label Attributes for Atomic Vectors | 0.1.2 | 0.1.2 |
laeken Estimation of Indicators on Social Exclusion and Poverty | 0.5.2 | 0.5.2 |
LaF Fast Access to Large ASCII Files | 0.8.4 | 0.8.4 |
lagged Classes and Methods for Lagged Objects | 0.3.2 | 0.3.2 |
lakemorpho Lake Morphometry Metrics | 1.1.1 | 1.1.1 |
LAM Some Latent Variable Models | 0.6-19 | 0.6-19 |
lambda.r Modeling Data with Functional Programming | 1.2.4 | 1.2.4 |
LambertW Probabilistic Models to Analyze and Gaussianize Heavy-Tailed, Skewed Data | 0.6.7 | 0.6.7 |
lamW Lambert-W Function | 2.1.2 | 2.1.2 |
landest Landmark Estimation of Survival and Treatment Effect | 1.1 | 1.1 |
landsat Radiometric and Topographic Correction of Satellite Imagery | 1.1.0 | 1.1.0 |
landscapemetrics Landscape Metrics for Categorical Map Patterns | 1.5.5 | 1.5.5 |
languagelayeR Access the 'languagelayer' API | 1.2.4 | 1.2.4 |
languageserver Language Server Protocol | 0.3.12 | 0.3.12 |
LaplacesDemon Complete Environment for Bayesian Inference | 16.1.6 | 16.1.6 |
LARF Local Average Response Functions for Instrumental Variable Estimation of Treatment Effects | 1.4 | 1.4 |
lars Least Angle Regression, Lasso and Forward Stagewise | 1.3 | 1.3 |
lasso2 L1 Constrained Estimation aka `lasso' | 1.2-22 | 1.2-22 |
lassoshooting L1 Regularized Regression (Lasso) Solver using the Cyclic Coordinate Descent Algorithm aka Lasso Shooting | 0.1.5-1.1 | 0.1.5-1.1 |
latdiag Draws Diagrams Useful for Checking Latent Scales | 0.3 | 0.3 |
latentnet Latent Position and Cluster Models for Statistical Networks | 2.10.6 | 2.10.6 |
later Utilities for Scheduling Functions to Execute Later with Event Loops | 1.3.0 | 1.3.0 |
latex2exp Use LaTeX Expressions in Plots | 0.9.4 | 0.9.4 |
lattice Trellis Graphics for R | 0.20-45 | 0.20-45 |
latticeExtra Extra Graphical Utilities Based on Lattice | 0.6-30 | 0.6-30 |
lava Latent Variable Models | 1.7.2.1 | 1.7.2.1 |
lava.tobit Latent Variable Models with Censored and Binary Outcomes | 0.5 | 0.5 |
lavaan Latent Variable Analysis | 0.6-13 | 0.6-13 |
lavaan.survey Complex Survey Structural Equation Modeling (SEM) | 1.1.3.1 | 1.1.3.1 |
lazyeval Lazy (Non-Standard) Evaluation | 0.2.2 | 0.2.2 |
lazyWeave LaTeX Wrappers for R Users | 3.0.2 | 3.0.2 |
lba Latent Budget Analysis for Compositional Data | 2.4.4 | 2.4.4 |
lbfgs Limited-memory BFGS Optimization | 1.2.1.2 | 1.2.1.2 |
lbfgsb3c Limited Memory BFGS Minimizer with Bounds on Parameters with optim() 'C' Interface | 2020-3.2 | 2020-3.2 |
lbiassurv Length-biased correction to survival curve estimation. | 1.1 | 1.1 |
LCA Localised Co-Dependency Analysis | 0.1.1 | 0.1.1 |
LCAvarsel Variable Selection for Latent Class Analysis | 1.1 | 1.1 |
lcda Latent Class Discriminant Analysis | 0.3.1 | 0.3.1 |
lcmm Extended Mixed Models Using Latent Classes and Latent Processes | 2.0.2 | 2.0.2 |
lcopula Liouville Copulas | 1.0.5 | 1.0.5 |
lda Collapsed Gibbs Sampling Methods for Topic Models | 1.4.2 | 1.4.2 |
ldat Large Data Sets | 0.3.3 | 0.3.3 |
ldbounds Lan-DeMets Method for Group Sequential Boundaries | 2.0.0 | 2.0.0 |
LDheatmap Graphical Display of Pairwise Linkage Disequilibria Between SNPs | 1.0-4 | 1.0-4 |
leafem 'leaflet' Extensions for 'mapview' | 0.1.6 | 0.1.6 |
leafgl High-Performance 'WebGl' Rendering for Package 'leaflet' | 0.1.1 | 0.1.1 |
leaflet Create Interactive Web Maps with the JavaScript 'Leaflet' Library | 2.1.2 | 2.1.2 |
leaflet.extras Extra Functionality for 'leaflet' Package | 1.0.0 | 1.0.0 |
leaflet.extras2 Extra Functionality for 'leaflet' Package | 1.1.0 | 1.1.0 |
leaflet.providers Leaflet Providers | 1.9.0 | 1.9.0 |
leafletR Interactive Web-Maps Based on the Leaflet JavaScript Library | 0.4-0 | 0.4-0 |
leafpm Leaflet Map Plugin for Drawing and Editing | 0.1.0 | 0.1.0 |
leafpop Include Tables, Images and Graphs in Leaflet Pop-Ups | 0.1.0 | 0.1.0 |
leafsync Small Multiples for Leaflet Web Maps | 0.1.0 | 0.1.0 |
leaps Regression Subset Selection | 3.1 | 3.1 |
LearnBayes Functions for Learning Bayesian Inference | 2.15.1 | 2.15.1 |
learnstats An Interactive Environment for Learning Statistics | 0.1.1 | 0.1.1 |
leastcostpath Modelling Pathways and Movement Potential Within a Landscape | 1.8.7 | 1.8.7 |
leiden R Implementation of Leiden Clustering Algorithm | 0.3.10 | 0.3.10 |
LexisNexisTools Working with Files from 'LexisNexis' | 0.3.5 | 0.3.5 |
LexisPlotR Plot Lexis Diagrams for Demographic Purposes | 0.4.0 | 0.4.0 |
lexRankr Extractive Summarization of Text with the LexRank Algorithm | 0.5.2 | 0.5.2 |
lfactors Factors with Levels | 1.0.4 | 1.0.4 |
lfe Linear Group Fixed Effects | 2.9-0 | 2.9-0 |
lfstat Calculation of Low Flow Statistics for Daily Stream Flow Data | 0.9.12 | 0.9.12 |
lgarch Simulation and Estimation of Log-GARCH Models | 0.6-2 | 0.6-2 |
lgcp Log-Gaussian Cox Process | 1.6 | 1.6 |
lgr A Fully Featured Logging Framework | 0.4.4 | 0.4.4 |
lgtdl A Set of Methods for Longitudinal Data Objects | 1.1.5 | 1.1.5 |
lhs Latin Hypercube Samples | 1.1.5 | 1.1.5 |
libcoin Linear Test Statistics for Permutation Inference | 1.0-9 | 1.0-9 |
LiblineaR Linear Predictive Models Based on the LIBLINEAR C/C++ Library | 2.10-22 | 2.10-22 |
librarian Install, Update, Load Packages from CRAN, 'GitHub', and 'Bioconductor' in One Step | 1.8.1 | 1.8.1 |
lifecontingencies Financial and Actuarial Mathematics for Life Contingencies | 1.3.9 | 1.3.9 |
lifecycle Manage the Life Cycle of your Package Functions | 1.0.3 | 1.0.3 |
LIHNPSD Poisson Subordinated Distribution | 0.2.1 | 0.2.1 |
limma Linear Models for Microarray Data | 3.52.0 | 3.52.0 |
limSolve Solving Linear Inverse Models | 1.5.6 | 1.5.6 |
LindleyPowerSeries Lindley Power Series Distribution | 1.0.1 | 1.0.1 |
linLIR linear Likelihood-based Imprecise Regression | 1.1 | 1.1 |
linpk Generate Concentration-Time Profiles from Linear PK Systems | 1.1.1 | 1.1.1 |
linprog Linear Programming / Optimization | 0.9-4 | 0.9-4 |
LinRegInteractive Interactive Interpretation of Linear Regression Models | 0.3-3 | 0.3-3 |
lintools Manipulation of Linear Systems of (in)Equalities | 0.1.7 | 0.1.7 |
lintr A 'Linter' for R Code | 2.0.1 | 2.0.1 |
lira LInear Regression in Astronomy | 2.0.1 | 2.0.1 |
lisp List-processing à la SRFI-1 | 0.1 | 0.1 |
lisrelToR Import Output from 'LISREL' into 'R' | 0.1.5 | 0.1.5 |
listcomp List Comprehensions | 0.4.1 | 0.4.1 |
listenv Environments Behaving (Almost) as Lists | 0.8.0 | 0.8.0 |
liteq Lightweight Portable Message Queue Using 'SQLite' | 1.1.0 | 1.1.0 |
livechatR R Wrapper for LiveChat REST API | 0.1.0 | 0.1.0 |
lle Locally linear embedding | 1.1 | 1.1 |
llogistic The L-Logistic Distribution | 1.0.3 | 1.0.3 |
lme4 Linear Mixed-Effects Models using 'Eigen' and S4 | 1.1-32 | 1.1-32 |
lmec Linear Mixed-Effects Models with Censored Responses | 1.0 | 1.0 |
lmerTest Tests in Linear Mixed Effects Models | 3.1-3 | 3.1-3 |
lmeSplines Add Smoothing Spline Modelling Capability to `nlme` | 1.1-12 | 1.1-12 |
lmm Linear Mixed Models | 1.3 | 1.3 |
lmodel2 Model II Regression | 1.7-3 | 1.7-3 |
lmom L-Moments | 2.9 | 2.9 |
lmomco L-Moments, Censored L-Moments, Trimmed L-Moments, L-Comoments, and Many Distributions | 2.4.7 | 2.4.7 |
Lmoments L-Moments and Quantile Mixtures | 1.3-1 | 1.3-1 |
lmomRFA Regional Frequency Analysis using L-Moments | 3.5 | 3.5 |
lmtest Testing Linear Regression Models | 0.9-40 | 0.9-40 |
LNIRT LogNormal Response Time Item Response Theory Models | 0.5.1 | 0.5.1 |
lobstr Visualize R Data Structures with Trees | 1.1.2 | 1.1.2 |
localsolver R API to LocalSolver | 2.3 | 2.3 |
locfit Local Regression, Likelihood and Density Estimation | 1.5-9.5 | 1.5-9.5 |
locits Test of Stationarity and Localized Autocovariance | 1.7.6 | 1.7.6 |
locpol Kernel Local Polynomial Regression | 0.8.0 | 0.8.0 |
lodi Limit of Detection Imputation for Single-Pollutant Models | 0.9.2 | 0.9.2 |
loe Local Ordinal Embedding | 1.1 | 1.1 |
logconcens Maximum Likelihood Estimation of a Log-Concave Density Based on Censored Data | 0.17-2 | 0.17-2 |
logcondens Estimate a Log-Concave Probability Density from Iid Observations | 2.1.6 | 2.1.6 |
logging R Logging Package | 0.10-108 | 0.10-108 |
logistf Firth's Bias-Reduced Logistic Regression | 1.24.1 | 1.24.1 |
logitnorm Functions for the Logitnormal Distribution | 0.8.38 | 0.8.38 |
loglognorm Double Log Normal Distribution Functions | 1.0.2 | 1.0.2 |
logmult Log-Multiplicative Models, Including Association Models | 0.7.4 | 0.7.4 |
logOfGamma Natural Logarithms of the Gamma Function for Large Values | 0.0.1 | 0.0.1 |
LogrankA Logrank Test for Aggregated Survival Data | 1.0 | 1.0 |
logspline Routines for Logspline Density Estimation | 2.1.19 | 2.1.19 |
lokern Kernel Regression Smoothing with Local or Global Plug-in Bandwidth | 1.1-10 | 1.1-10 |
lomb Lomb-Scargle Periodogram | 2.1.0 | 2.1.0 |
longitudinal Analysis of Multiple Time Course Data | 1.1.13 | 1.1.13 |
longitudinalData Longitudinal Data | 2.4.5 | 2.4.5 |
longmemo Statistics for Long-Memory Processes (Book Jan Beran), and Related Functionality | 1.1-2 | 1.1-2 |
LongMemoryTS Long Memory Time Series | 0.1.0 | 0.1.0 |
longurl Expand Short 'URLs' | 0.3.3 | 0.3.3 |
loo Efficient Leave-One-Out Cross-Validation and WAIC for Bayesian Models | 2.5.1 | 2.5.1 |
lordif Logistic Ordinal Regression Differential Item Functioning using IRT | 0.3-3 | 0.3-3 |
lori Imputation of High-Dimensional Count Data using Side Information | 2.2.2 | 2.2.2 |
lotri A Simple Way to Specify Symmetric, Block Diagonal Matrices | 0.4.3 | 0.4.3 |
LowRankQP Low Rank Quadratic Programming | 1.0.5 | 1.0.5 |
lpc Lassoed Principal Components for Testing Significance of Features | 1.0.2.1 | 1.0.2.1 |
lpirfs Local Projections Impulse Response Functions | 0.2.2 | 0.2.2 |
LPM Linear Parametric Models Applied to Hydrological Series | 2.9 | 2.9 |
lpSolve Interface to 'Lp_solve' v. 5.5 to Solve Linear/Integer Programs | 5.6.18 | 5.6.18 |
lpSolveAPI R Interface to 'lp_solve' Version 5.5.2.0 | 5.5.2.0-17.9 | 5.5.2.0-17.9 |
LPStimeSeries Learned Pattern Similarity and Representation for Time Series | 1.0-5 | 1.0-5 |
lqmm Linear Quantile Mixed Models | 1.5.8 | 1.5.8 |
lsa Latent Semantic Analysis | 0.73.3 | 0.73.3 |
lsei Solving Least Squares or Quadratic Programming Problems under Equality/Inequality Constraints | 1.3-0 | 1.3-0 |
lsl Latent Structure Learning | 0.5.6 | 0.5.6 |
lslx Semi-Confirmatory Structural Equation Modeling via Penalized Likelihood or Least Squares | 0.6.11 | 0.6.11 |
lsmeans Least-Squares Means | 2.30-0 | 2.30-0 |
LSMonteCarlo American options pricing with Least Squares Monte Carlo method | 1.0 | 1.0 |
lspls LS-PLS Models | 0.2-2 | 0.2-2 |
ltbayes Simulation-Based Bayesian Inference for Latent Traits of Item Response Models | 0.4 | 0.4 |
ltm Latent Trait Models under IRT | 1.2-0 | 1.2-0 |
LTRCtrees Survival Trees to Fit Left-Truncated and Right-Censored and Interval-Censored Survival Data | 1.1.1 | 1.1.1 |
ltsa Linear Time Series Analysis | 1.4.6 | 1.4.6 |
lubridate Make Dealing with Dates a Little Easier | 1.9.2 | 1.9.2 |
lucid Printing Floating Point Numbers in a Human-Friendly Format | 1.8 | 1.8 |
lulcc Land Use Change Modelling in R | 1.0.4 | 1.0.4 |
Luminescence Comprehensive Luminescence Dating Data Analysis | 0.9.19 | 0.9.19 |
lutz Look Up Time Zones of Point Coordinates | 0.3.1 | 0.3.1 |
lvec Out of Memory Vectors | 0.2.2 | 0.2.2 |
lvnet Latent Variable Network Modeling | 0.3.5 | 0.3.5 |
lvplot Letter Value 'Boxplots' | 0.2.1 | 0.2.1 |
lwgeom Bindings to Selected 'liblwgeom' Functions for Simple Features | 0.2-8 | 0.2-8 |
m2b Movement to Behaviour Inference using Random Forest | 1.0 | 1.0 |
m2r Interface to 'Macaulay2' | 1.0.2 | 1.0.2 |
M3 Reading M3 files | 0.3 | 0.3 |
MAc Meta-Analysis with Correlations | 1.1.1 | 1.1.1 |
MAd Meta-Analysis with Mean Differences | 0.8-3 | 0.8-3 |
mada Meta-Analysis of Diagnostic Accuracy | 0.5.10 | 0.5.10 |
madrat May All Data be Reproducible and Transparent (MADRaT) * | 2.3.2 | 2.3.2 |
mafs Multiple Automatic Forecast Selection | 0.0.3 | 0.0.3 |
magclass Data Class and Tools for Handling Spatial-Temporal Data | 6.0.9 | 6.0.9 |
magic Create and Investigate Magic Squares | 1.6-1 | 1.6-1 |
magicaxis Pretty Scientific Plotting with Minor-Tick and Log Minor-Tick Support | 2.2.14 | 2.2.14 |
magick Advanced Graphics and Image-Processing in R | 2.7.4 | 2.7.4 |
magrittr A Forward-Pipe Operator for R | 2.0.3 | 2.0.3 |
mailR A Utility to Send Emails from R | 0.8 | 0.8 |
makeProject Creates an empty package framework for the LCFD format | 1.0 | 1.0 |
MALDIquant Quantitative Analysis of Mass Spectrometry Data | 1.22.1 | 1.22.1 |
MALDIquantForeign Import/Export Routines for 'MALDIquant' | 0.13 | 0.13 |
MALDIrppa MALDI Mass Spectrometry Data Robust Pre-Processing and Analysis | 1.1.0 | 1.1.0 |
MAMSE Calculation of Minimum Averaged Mean Squared Error (MAMSE) Weights | 0.2-1 | 0.2-1 |
manhattanly Interactive Q-Q and Manhattan Plots Using 'plotly.js' | 0.3.0 | 0.3.0 |
ManifoldOptim An R Interface to the 'ROPTLIB' Library for Riemannian Manifold Optimization | 1.0.1 | 1.0.1 |
manipulate Interactive Plots for RStudio | 1.0.1 | 1.0.1 |
MAPA Multiple Aggregation Prediction Algorithm | 2.0.5 | 2.0.5 |
mapdata Extra Map Databases | 2.3.1 | 2.3.1 |
mapdeck Interactive Maps Using 'Mapbox GL JS' and 'Deck.gl' | 0.3.4 | 0.3.4 |
mapedit Interactive Editing of Spatial Data in R | 0.6.0 | 0.6.0 |
mapiso Create Contour Polygons from Regular Grids | 0.2.0 | 0.2.0 |
mapproj Map Projections | 1.2.11 | 1.2.11 |
maps Draw Geographical Maps | 3.4.1 | 3.4.1 |
mapsapi 'sf'-Compatible Interface to 'Google Maps' APIs | 0.5.3 | 0.5.3 |
mapsf Thematic Cartography | 0.4.0 | 0.4.0 |
mapStats Geographic Display of Survey Data Statistics | 2.4 | 2.4 |
maptools Tools for Handling Spatial Objects | 1.1-4 | 1.1-4 |
maptree Mapping, Pruning, and Graphing Tree Models | 1.4-8 | 1.4-8 |
mapview Interactive Viewing of Spatial Data in R | 2.10.0 | 2.10.0 |
mAr Multivariate AutoRegressive Analysis | 1.2-0 | 1.2-0 |
mar1s Multiplicative AR(1) with Seasonal Processes | 2.1.1 | 2.1.1 |
marcher Migration and Range Change Estimation in R | 0.0-2 | 0.0-2 |
marg Approximate Marginal Inference for Regression-Scale Models | 1.2-2.1 | 1.2-2.1 |
margins Marginal Effects for Model Objects | 0.3.26 | 0.3.26 |
marima Multivariate ARIMA and ARIMA-X Analysis | 2.2 | 2.2 |
markdown Render Markdown with 'commonmark' | 1.5 | 1.5 |
marked Mark-Recapture Analysis for Survival and Abundance Estimation | 1.2.6 | 1.2.6 |
markophylo Markov Chain Models for Phylogenetic Trees | 1.0.8 | 1.0.8 |
markovchain Easy Handling Discrete Time Markov Chains | 0.9.1 | 0.9.1 |
MarkowitzR Statistical Significance of the Markowitz Portfolio | 1.0.2 | 1.0.2 |
marmap Import, Plot and Analyze Bathymetric and Topographic Data | 1.0.9 | 1.0.9 |
marqLevAlg A Parallelized General-Purpose Optimization Based on Marquardt-Levenberg Algorithm | 2.0.7 | 2.0.7 |
MARSS Multivariate Autoregressive State-Space Modeling | 3.11.4 | 3.11.4 |
MASS Support Functions and Datasets for Venables and Ripley's MASS | 7.3-58.3 | 7.3-58.3 |
MassSpecWavelet | 1.62.0 | 1.62.0 |
Matching Multivariate and Propensity Score Matching with Balance Optimization | 4.10-8 | 4.10-8 |
matchingMarkets Analysis of Stable Matchings | 1.0-2 | 1.0-2 |
matchingR Matching Algorithms in R and C++ | 1.3.3 | 1.3.3 |
MatchIt Nonparametric Preprocessing for Parametric Causal Inference | 4.3.4 | 4.3.4 |
MatchThem Matching and Weighting Multiply Imputed Datasets | 1.0.1 | 1.0.1 |
mathjaxr Using 'Mathjax' in Rd Files | 1.6-0 | 1.6-0 |
mathpix Support for the 'Mathpix' API (Image to 'LaTeX') | 0.5.0 | 0.5.0 |
matlab 'MATLAB' Emulation Package | 1.0.4 | 1.0.4 |
matlib Matrix Functions for Teaching and Learning Linear Algebra and Multivariate Statistics | 0.9.5 | 0.9.5 |
Matrix Sparse and Dense Matrix Classes and Methods | 1.5-3 | 1.5-3 |
matrixcalc Collection of Functions for Matrix Calculations | 1.0-5 | 1.0-5 |
MatrixExtra Extra Methods for Sparse Matrices | 0.1.13 | 0.1.13 |
MatrixGenerics | 1.8.0 | 1.8.0 |
MatrixModels Modelling with Sparse and Dense Matrices | 0.5-1 | 0.5-1 |
matrixNormal The Matrix Normal Distribution | 0.1.1 | 0.1.1 |
matrixsampling Simulations of Matrix Variate Distributions | 2.0.0 | 2.0.0 |
matrixStats Functions that Apply to Rows and Columns of Matrices (and to Vectors) | 0.62.0 | 0.62.0 |
MAVIS Meta Analysis via Shiny | 1.1.3 | 1.1.3 |
maxLik Maximum Likelihood Estimation and Related Tools | 1.5-2 | 1.5-2 |
maxnet Fitting 'Maxent' Species Distribution Models with 'glmnet' | 0.1.4 | 0.1.4 |
maxstat Maximally Selected Rank Statistics | 0.7-25 | 0.7-25 |
MBA Multilevel B-Spline Approximation | 0.1-0 | 0.1-0 |
mbbefd Maxwell Boltzmann Bose Einstein Fermi Dirac Distribution and Destruction Rate Modelling | 0.8.10 | 0.8.10 |
MBC Multivariate Bias Correction of Climate Model Outputs | 0.10-5 | 0.10-5 |
mbend Matrix Bending | 1.3.1 | 1.3.1 |
MBESS The MBESS R Package | 4.9.1 | 4.9.1 |
MBHdesign Spatial Designs for Ecological and Environmental Surveys | 2.2.2 | 2.2.2 |
mblm Median-Based Linear Models | 0.12.1 | 0.12.1 |
MBNMAdose Dose-Response MBNMA Models | 0.4.1 | 0.4.1 |
MBNMAtime Run Time-Course Model-Based Network Meta-Analysis (MBNMA) Models | 0.2.1 | 0.2.1 |
mboost Model-Based Boosting | 2.9-7 | 2.9-7 |
MBSP Multivariate Bayesian Model with Shrinkage Priors | 3.0 | 3.0 |
mbsts Multivariate Bayesian Structural Time Series | 3.0 | 3.0 |
mc.heterogeneity A Monte Carlo Based Heterogeneity Test for Meta-Analysis | 0.1.2 | 0.1.2 |
mc2d Tools for Two-Dimensional Monte-Carlo Simulations | 0.1-22 | 0.1-22 |
MCAvariants Multiple Correspondence Analysis Variants | 2.6 | 2.6 |
mcclust Process an MCMC Sample of Clusterings | 1.0.1 | 1.0.1 |
mcga Machine Coded Genetic Algorithms for Real-Valued Optimization Problems | 3.0.3 | 3.0.3 |
mcGlobaloptim Global optimization using Monte Carlo and Quasi Monte Carlo<U+000a>simulation | 0.1 | 0.1 |
mclcar Estimating Conditional Auto-Regressive (CAR) Models using Monte Carlo Likelihood Methods | 0.1-9 | 0.1-9 |
mclust Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation | 6.0.0 | 6.0.0 |
mcmc Markov Chain Monte Carlo | 0.9-7 | 0.9-7 |
MCMCglmm MCMC Generalised Linear Mixed Models | 2.34 | 2.34 |
MCMCpack Markov Chain Monte Carlo (MCMC) Package | 1.6-3 | 1.6-3 |
mcmcplots Create Plots from MCMC Output | 0.4.3 | 0.4.3 |
mcmcr Manipulate MCMC Samples | 0.6.1 | 0.6.1 |
mcmcse Monte Carlo Standard Errors for MCMC | 1.5-0 | 1.5-0 |
mco Multiple Criteria Optimization Algorithms and Related Functions | 1.15.6 | 1.15.6 |
Mcomp Data from the M-Competitions | 2.8 | 2.8 |
mcompanion Objects and Methods for Multi-Companion Matrices | 0.5.5 | 0.5.5 |
MCPMod Design and Analysis of Dose-Finding Studies | 1.0-10.1 | 1.0-10.1 |
McSpatial Nonparametric spatial data analysis | 2.0 | 2.0 |
mda Mixture and Flexible Discriminant Analysis | 0.5-3 | 0.5-3 |
mded Measuring the Difference Between Two Empirical Distributions | 0.1-2 | 0.1-2 |
mdftracks Read and Write 'MTrackJ Data Files' | 0.2.1 | 0.2.1 |
mdmb Model Based Treatment of Missing Data | 1.8-7 | 1.8-7 |
measurementProtocol Send Data from R to the Measurement Protocol | 0.1.1 | 0.1.1 |
measurements Tools for Units of Measurement | 1.5.0 | 1.5.0 |
measures Performance Measures for Statistical Learning | 0.3 | 0.3 |
meboot Maximum Entropy Bootstrap for Time Series | 1.4-9.2 | 1.4-9.2 |
Mediana Clinical Trial Simulations | 1.0.8 | 1.0.8 |
mediation Causal Mediation Analysis | 4.5.0 | 4.5.0 |
mefa Multivariate Data Handling in Ecology and Biogeography | 3.2-8 | 3.2-8 |
memisc Management of Survey Data and Presentation of Analysis Results | 0.99.31.6 | 0.99.31.6 |
memoise 'Memoisation' of Functions | 2.0.1 | 2.0.1 |
MendelianRandomization Mendelian Randomization Package | 0.7.0 | 0.7.0 |
MEPDF Creation of Empirical Density Functions Based on Multivariate Data | 3.0 | 3.0 |
MESS Miscellaneous Esoteric Statistical Scripts | 0.5.9 | 0.5.9 |
meta General Package for Meta-Analysis | 6.2-1 | 6.2-1 |
meta4diag Meta-Analysis for Diagnostic Test Studies | 2.1.1 | 2.1.1 |
MetaAnalyser An Interactive Visualisation of Meta-Analysis as a Physical Weighing Machine | 0.2.1 | 0.2.1 |
MetABEL Meta-analysis of genome-wide SNP association results | 0.2-0 | 0.2-0 |
metabias Meta-Analysis for Within-Study and/or Across-Study Biases | 0.1.0 | 0.1.0 |
metaBLUE BLUE for Combining Location and Scale Information in a Meta-Analysis | 1.0.0 | 1.0.0 |
MetabolAnalyze Probabilistic latent variable models for metabolomic data. | 1.3.1 | 1.3.1 |
metacart Meta-CART: A Flexible Approach to Identify Moderators in Meta-Analysis | 2.0-3 | 2.0-3 |
metacoder Tools for Parsing, Manipulating, and Graphing Taxonomic Abundance Data | 0.3.5 | 0.3.5 |
metacom Analysis of the 'Elements of Metacommunity Structure' | 1.5.3 | 1.5.3 |
metacor Meta-Analysis of Correlation Coefficients | 1.0-2.1 | 1.0-2.1 |
metadat Meta-Analysis Datasets | 1.2-0 | 1.2-0 |
metaDigitise Extract and Summarise Data from Published Figures | 1.0.1 | 1.0.1 |
metafor Meta-Analysis Package for R | 4.0-0 | 4.0-0 |
metaforest Exploring Heterogeneity in Meta-Analysis using Random Forests | 0.1.3 | 0.1.3 |
metafuse Fused Lasso Approach in Regression Coefficient Clustering | 2.0-1 | 2.0-1 |
metagam Meta-Analysis of Generalized Additive Models | 0.3.1 | 0.3.1 |
metagear Comprehensive Research Synthesis Tools for Systematic Reviews and Meta-Analysis | 0.7 | 0.7 |
metagen Inference in Meta Analysis and Meta Regression | 1.0 | 1.0 |
metaheuristicOpt Metaheuristic for Optimization | 2.0.0 | 2.0.0 |
MetaIntegrator Meta-Analysis of Gene Expression Data | 2.1.3 | 2.1.3 |
metaLik Likelihood Inference in Meta-Analysis and Meta-Regression Models | 0.43.0 | 0.43.0 |
metaMA Meta-Analysis for MicroArrays | 3.1.3 | 3.1.3 |
metamedian Meta-Analysis of Medians | 1.0.0 | 1.0.0 |
metamisc Meta-Analysis of Diagnosis and Prognosis Research Studies | 0.4.0 | 0.4.0 |
metansue Meta-Analysis of Studies with Non-Statistically Significant Unreported Effects | 2.5 | 2.5 |
metap Meta-Analysis of Significance Values | 1.8 | 1.8 |
MetaPath Perform the Meta-Analysis for Pathway Enrichment Analysis (MAPE) | 1.0 | 1.0 |
MetaPCA MetaPCA: Meta-analysis in the Dimension Reduction of Genomic data | 0.1.4 | 0.1.4 |
metaplotr Creates CrossHairs Plots for Meta-Analyses | 0.0.3 | 0.0.3 |
metaplus Robust Meta-Analysis and Meta-Regression | 1.0-4 | 1.0-4 |
metapod | 1.4.0 | 1.4.0 |
metapro Robust P-Value Combination Methods | 1.5.8 | 1.5.8 |
metaRMST Meta-Analysis of RMSTD | 1.0.0 | 1.0.0 |
metaRNASeq Meta-Analysis of RNA-Seq Data | 1.0.7 | 1.0.7 |
metaSEM Meta-Analysis using Structural Equation Modeling | 1.3.0 | 1.3.0 |
metasens Statistical Methods for Sensitivity Analysis in Meta-Analysis | 1.5-2 | 1.5-2 |
MetaSKAT Meta Analysis for SNP-Set (Sequence) Kernel Association Test | 0.82 | 0.82 |
MetaSubtract Subtracting Summary Statistics of One or more Cohorts from Meta-GWAS Results | 1.60 | 1.60 |
metatest Fit and Test Metaregression Models | 1.0-5 | 1.0-5 |
Metatron Meta-analysis for Classification Data and Correction to Imperfect Reference | 0.1-1 | 0.1-1 |
MetaUtility Utility Functions for Conducting and Interpreting Meta-Analyses | 2.1.2 | 2.1.2 |
metavcov Computing Variances and Covariances, Visualization and Missing Data Solution for Multivariate Meta-Analysis | 2.1.4 | 2.1.4 |
metaviz Forest Plots, Funnel Plots, and Visual Funnel Plot Inference for Meta-Analysis | 0.3.1 | 0.3.1 |
metawho Meta-Analytical Implementation to Identify Who Benefits Most from Treatments | 0.2.0 | 0.2.0 |
meteo Spatio-Temporal Analysis and Mapping of Meteorological Observations | 0.1-5 | 0.1-5 |
meteoland Landscape Meteorology Tools | 0.9.7 | 0.9.7 |
meteospain Access to Spanish Meteorological Stations Services | 0.1.1 | 0.1.1 |
methods | 4.2.3 | 4.2.3 |
Metrics Evaluation Metrics for Machine Learning | 0.1.4 | 0.1.4 |
metRology Support for Metrological Applications | 0.9-28-1 | 0.9-28-1 |
mets Analysis of Multivariate Event Times | 1.3.1 | 1.3.1 |
mev Modelling of Extreme Values | 1.14 | 1.14 |
mexhaz Mixed Effect Excess Hazard Models | 2.4 | 2.4 |
mFilter Miscellaneous Time Series Filters | 0.1-5 | 0.1-5 |
mfp Multivariable Fractional Polynomials | 1.5.2.2 | 1.5.2.2 |
mfx Marginal Effects, Odds Ratios and Incidence Rate Ratios for GLMs | 1.2-2 | 1.2-2 |
mgcv Mixed GAM Computation Vehicle with Automatic Smoothness Estimation | 1.8-42 | 1.8-42 |
mgcViz Visualisations for Generalized Additive Models | 0.1.9 | 0.1.9 |
mgm Estimating Time-Varying k-Order Mixed Graphical Models | 1.2-13 | 1.2-13 |
mgpd mgpd: Functions for multivariate generalized Pareto distribution (MGPD of Type II) | 1.99 | 1.99 |
MHadaptive General Markov Chain Monte Carlo for Bayesian Inference using<U+000a>adaptive Metropolis-Hastings sampling | 1.1-8 | 1.1-8 |
mhsmm Inference for Hidden Markov and Semi-Markov Models | 0.4.16 | 0.4.16 |
mhurdle Multiple Hurdle Tobit Models | 1.3-0 | 1.3-0 |
mi Missing Data Imputation and Model Checking | 1.1 | 1.1 |
mice Multivariate Imputation by Chained Equations | 3.15.0 | 3.15.0 |
miceadds Some Additional Multiple Imputation Functions, Especially for 'mice' | 3.16-18 | 3.16-18 |
micEcon Microeconomic Analysis and Modelling | 0.6-18 | 0.6-18 |
micEconAids Demand Analysis with the Almost Ideal Demand System (AIDS) | 0.6-20 | 0.6-20 |
micEconCES Analysis with the Constant Elasticity of Substitution (CES) Function | 1.0-2 | 1.0-2 |
micEconIndex Price and Quantity Indices | 0.1-8 | 0.1-8 |
miceFast Fast Imputations Using 'Rcpp' and 'Armadillo' | 0.8.1 | 0.8.1 |
micemd Multiple Imputation by Chained Equations with Multilevel Data | 1.8.0 | 1.8.0 |
miceMNAR Missing not at Random Imputation Models for Multiple Imputation by Chained Equation | 1.0.2 | 1.0.2 |
miceRanger Multiple Imputation by Chained Equations with Random Forests | 1.5.0 | 1.5.0 |
miCoPTCM Promotion Time Cure Model with Mis-Measured Covariates | 1.1 | 1.1 |
microbenchmark Accurate Timing Functions | 1.4.9 | 1.4.9 |
microdemic 'Microsoft Academic' API Client | 0.6.0 | 0.6.0 |
micromap Linked Micromap Plots | 1.9.5 | 1.9.5 |
microsamplingDesign Finding Optimal Microsampling Designs for Non-Compartmental Pharmacokinetic Analysis | 1.0.8 | 1.0.8 |
MicSim Performing Continuous-Time Microsimulation | 2.0.0 | 2.0.0 |
midasr Mixed Data Sampling Regression | 0.8 | 0.8 |
MIICD Multiple Imputation for Interval Censored Data | 2.4 | 2.4 |
MIIVsem Model Implied Instrumental Variable (MIIV) Estimation of Structural Equation Models | 0.5.8 | 0.5.8 |
mime Map Filenames to MIME Types | 0.12 | 0.12 |
mimi Main Effects and Interactions in Mixed and Incomplete Data | 0.2.0 | 0.2.0 |
MImix Mixture summary method for multiple imputation | 1.0 | 1.0 |
minerva Maximal Information-Based Nonparametric Exploration for Variable Analysis | 1.5.10 | 1.5.10 |
miniCRAN Create a Mini Version of CRAN Containing Only Selected Packages | 0.2.16 | 0.2.16 |
minidown Create Simple Yet Powerful HTML Documents with Light Weight CSS Frameworks | 0.4.0 | 0.4.0 |
minimax The Minimax Distribution Family | 1.1 | 1.1 |
miniMeta Web Application to Run Meta-Analyses | 0.2 | 0.2 |
miniUI Shiny UI Widgets for Small Screens | 0.1.1.1 | 0.1.1.1 |
minpack.lm R Interface to the Levenberg-Marquardt Nonlinear Least-Squares Algorithm Found in MINPACK, Plus Support for Bounds | 1.2-3 | 1.2-3 |
minqa Derivative-Free Optimization Algorithms by Quadratic Approximation | 1.2.5 | 1.2.5 |
mipfp Multidimensional Iterative Proportional Fitting and Alternative Models | 3.2.1 | 3.2.1 |
mipred Prediction using Multiple Imputation | 0.0.1 | 0.0.1 |
mirt Multidimensional Item Response Theory | 1.38.1 | 1.38.1 |
mirtCAT Computerized Adaptive Testing with Multidimensional Item Response Theory | 1.12.2 | 1.12.2 |
misaem Linear Regression and Logistic Regression with Missing Covariates | 1.0.1 | 1.0.1 |
misc3d Miscellaneous 3D Plots | 0.9-1 | 0.9-1 |
miscF Miscellaneous Functions | 0.1-5 | 0.1-5 |
miscTools Miscellaneous Tools and Utilities | 0.6-26 | 0.6-26 |
missCompare Intuitive Missing Data Imputation Framework | 1.0.3 | 1.0.3 |
missForest Nonparametric Missing Value Imputation using Random Forest | 1.5 | 1.5 |
missingHE Missing Outcome Data in Health Economic Evaluation | 1.4.1 | 1.4.1 |
missMDA Handling Missing Values with Multivariate Data Analysis | 1.18 | 1.18 |
MissMech Testing Homoscedasticity, Multivariate Normality, and Missing Completely at Random | 1.0.2 | 1.0.2 |
missSBM Handling Missing Data in Stochastic Block Models | 1.0.3 | 1.0.3 |
MitISEM Mixture of Student t Distributions using Importance Sampling and Expectation Maximization | 1.2 | 1.2 |
mitml Tools for Multiple Imputation in Multilevel Modeling | 0.4-5 | 0.4-5 |
mitools Tools for Multiple Imputation of Missing Data | 2.4 | 2.4 |
MittagLeffleR Mittag-Leffler Family of Distributions | 0.4.1 | 0.4.1 |
miWQS Multiple Imputation Using Weighted Quantile Sum Regression | 0.4.4 | 0.4.4 |
mix Estimation/Multiple Imputation for Mixed Categorical and Continuous Data | 1.0-11 | 1.0-11 |
mixAK Multivariate Normal Mixture Models and Mixtures of Generalized Linear Mixed Models Including Model Based Clustering | 5.5 | 5.5 |
MixAll Clustering and Classification using Model-Based Mixture Models | 1.5.1 | 1.5.1 |
mixdist Finite Mixture Distribution Models | 0.5-5 | 0.5-5 |
MixedTS Mixed Tempered Stable Distribution | 1.0.4 | 1.0.4 |
mixmeta An Extended Mixed-Effects Framework for Meta-Analysis | 1.2.0 | 1.2.0 |
mixPHM Mixtures of Proportional Hazard Models | 0.7-2 | 0.7-2 |
mixRasch Mixture Rasch Models with JMLE | 1.1 | 1.1 |
mixreg Functions to Fit Mixtures of Regressions | 2.0-10 | 2.0-10 |
MixSim Simulating Data to Study Performance of Clustering Algorithms | 1.1-6 | 1.1-6 |
mixsmsn Fitting Finite Mixture of Scale Mixture of Skew-Normal Distributions | 1.1-10 | 1.1-10 |
mixtools Tools for Analyzing Finite Mixture Models | 1.2.0 | 1.2.0 |
mixture Mixture Models for Clustering and Classification | 2.0.5 | 2.0.5 |
mize Unconstrained Numerical Optimization Algorithms | 0.2.4 | 0.2.4 |
mkde 2D and 3D movement-based kernel density estimates (MKDEs). | 0.1 | 0.1 |
mkin Kinetic Evaluation of Chemical Degradation Data | 1.1.0 | 1.1.0 |
mknapsack Multiple Knapsack Problem Solver | 0.1.0 | 0.1.0 |
mlapi Abstract Classes for Building 'scikit-learn' Like API | 0.1.1 | 0.1.1 |
mlbench Machine Learning Benchmark Problems | 2.1-3 | 2.1-3 |
MLCIRTwithin Latent Class Item Response Theory (LC-IRT) Models under Within-Item Multidimensionality | 2.1.1 | 2.1.1 |
MLDS Maximum Likelihood Difference Scaling | 0.4.901 | 0.4.901 |
mleap Interface to 'MLeap' | 1.1.0 | 1.1.0 |
MLEcens Computation of the MLE for Bivariate Interval Censored Data | 0.1-7 | 0.1-7 |
MLmetrics Machine Learning Evaluation Metrics | 1.1.1 | 1.1.1 |
mlmRev Examples from Multilevel Modelling Software Review | 1.0-8 | 1.0-8 |
mlogit Multinomial Logit Models | 1.1-1 | 1.1-1 |
mlogitBMA Bayesian Model Averaging for Multinomial Logit Models | 0.1-7 | 0.1-7 |
mlr Machine Learning in R | 2.19.1 | 2.19.1 |
mlr3 Machine Learning in R - Next Generation | 0.13.3 | 0.13.3 |
mlr3measures Performance Measures for 'mlr3' | 0.5.0 | 0.5.0 |
mlr3misc Helper Functions for 'mlr3' | 0.11.0 | 0.11.0 |
mlrMBO Bayesian Optimization and Model-Based Optimization of Expensive Black-Box Functions | 1.1.5.1 | 1.1.5.1 |
mlt Most Likely Transformations | 1.4-1 | 1.4-1 |
mltools Machine Learning Tools | 0.3.5 | 0.3.5 |
mlVAR Multi-Level Vector Autoregression | 0.5 | 0.5 |
MM The Multiplicative Multinomial Distribution | 1.6-6 | 1.6-6 |
mmand Mathematical Morphology in Any Number of Dimensions | 1.6.3 | 1.6.3 |
mmap Map Pages of Memory | 0.6-21 | 0.6-21 |
mmeta Multivariate Meta-Analysis | 3.0.0 | 3.0.0 |
mnlogit Multinomial Logit Model | 1.2.6 | 1.2.6 |
mnormpow Multivariate Normal Distributions with Power Integrand | 0.1.1 | 0.1.1 |
mnormt The Multivariate Normal and t Distributions, and Their Truncated Versions | 2.1.1 | 2.1.1 |
MOCCA Multi-Objective Optimization for Collecting Cluster Alternatives | 1.4 | 1.4 |
mockery Mocking Library for R | 0.4.3 | 0.4.3 |
mockr Mocking in R | 0.2.0 | 0.2.0 |
modeest Mode Estimation | 2.4.0 | 2.4.0 |
modeldata Data Sets Useful for Modeling Examples | 1.1.0 | 1.1.0 |
modelfree Model-free estimation of a psychometric function | 1.1-1 | 1.1-1 |
ModelMap Modeling and Map Production using Random Forest and Related Stochastic Models | 3.4.0.3 | 3.4.0.3 |
ModelMetrics Rapid Calculation of Model Metrics | 1.2.2.2 | 1.2.2.2 |
modelr Modelling Functions that Work with the Pipe | 0.1.10 | 0.1.10 |
modeltools Tools and Classes for Statistical Models | 0.2-23 | 0.2-23 |
moderndive Tidyverse-Friendly Introductory Linear Regression | 0.5.5 | 0.5.5 |
MODIS Acquisition and Processing of MODIS Products | 1.2.2 | 1.2.2 |
MODISTools Interface to the 'MODIS Land Products Subsets' Web Services | 1.1.4 | 1.1.4 |
MODIStsp Find, Download and Process MODIS Land Products Data | 1.4.0 | 1.4.0 |
modules Self Contained Units of Source Code | 0.10.0 | 0.10.0 |
MoEClust Gaussian Parsimonious Clustering Models with Covariates and a Noise Component | 1.5.0 | 1.5.0 |
mokken Conducts Mokken Scale Analysis | 3.0.6 | 3.0.6 |
mombf Model Selection with Bayesian Methods and Information Criteria | 3.3.1 | 3.3.1 |
moments Moments, Cumulants, Skewness, Kurtosis and Related Tests | 0.14.1 | 0.14.1 |
MomTrunc Moments of Folded and Doubly Truncated Multivariate Distributions | 6.0 | 6.0 |
mondate Keep Track of Dates in Terms of Months | 0.10.02 | 0.10.02 |
MonetDB.R Connect MonetDB to R | 2.0.0 | 2.0.0 |
MonetDBLite In-Process Version of 'MonetDB' | 0.6.0 | 0.6.0 |
mongolite Fast and Simple 'MongoDB' Client for R | 2.7.1 | 2.7.1 |
monkeylearn Accesses the Monkeylearn API for Text Classifiers and Extractors | 0.2.0 | 0.2.0 |
MonoPoly Functions to Fit Monotone Polynomials | 0.3-10 | 0.3-10 |
moonBook Functions and Datasets for the Book by Keon-Woong Moon | 0.3.1 | 0.3.1 |
Morpho Calculations and Visualisations Related to Geometric Morphometrics | 2.11 | 2.11 |
mosaic Project MOSAIC Statistics and Mathematics Teaching Utilities | 1.8.4.2 | 1.8.4.2 |
mosaicCore Common Utilities for Other MOSAIC-Family Packages | 0.9.2.1 | 0.9.2.1 |
mosaicData Project MOSAIC Data Sets | 0.20.3 | 0.20.3 |
MOTE Effect Size and Confidence Interval Calculator | 1.0.2 | 1.0.2 |
mousetrack Mouse-Tracking Measures from Trajectory Data | 1.0.0 | 1.0.0 |
mousetrap Process and Analyze Mouse-Tracking Data | 3.2.1 | 3.2.1 |
move Visualizing and Analyzing Animal Track Data | 4.0.6 | 4.0.6 |
movecost Calculation of Slope-Dependant Accumulated Cost Surface, Least-Cost Paths, Least-Cost Corridors, Least-Cost Networks Related to Human Movement Across the Landscape | 1.9 | 1.9 |
moveHMM Animal Movement Modelling using Hidden Markov Models | 1.8 | 1.8 |
moveWindSpeed Estimate Wind Speeds from Bird Trajectories | 0.2.3 | 0.2.3 |
movMF Mixtures of von Mises-Fisher Distributions | 0.2-7 | 0.2-7 |
MPDiR Data Sets and Scripts for Modeling Psychophysical Data in R | 0.1-20 | 0.1-20 |
MplusAutomation An R Package for Facilitating Large-Scale Latent Variable Analyses in Mplus | 1.1.0 | 1.1.0 |
mpoly Symbolic Computation and More with Multivariate Polynomials | 1.1.1 | 1.1.1 |
MPSEM Modeling Phylogenetic Signals using Eigenvector Maps | 0.4-1 | 0.4-1 |
mpt Multinomial Processing Tree Models | 0.8-0 | 0.8-0 |
MPTinR Analyze Multinomial Processing Tree Models | 1.14.1 | 1.14.1 |
MPV Data Sets from Montgomery, Peck and Vining | 1.62 | 1.62 |
mQTL Metabolomic Quantitative Trait Locus Mapping | 1.0 | 1.0 |
mrds Mark-Recapture Distance Sampling | 2.2.8 | 2.2.8 |
mrfDepth Depth Measures in Multivariate, Regression and Functional Settings | 1.0.13 | 1.0.13 |
mrgsolve Simulate from ODE-Based Models | 1.0.9 | 1.0.9 |
mritc MRI Tissue Classification | 0.5-3 | 0.5-3 |
MRsurv A multiplicative-regression model for relative survival. | 0.2 | 0.2 |
mscstexta4r R Client for the Microsoft Cognitive Services Text Analytics REST API | 0.1.2 | 0.1.2 |
mscsweblm4r R Client for the Microsoft Cognitive Services Web Language Model REST API | 0.1.2 | 0.1.2 |
MSGARCH Markov-Switching GARCH Models | 2.51 | 2.51 |
msImpute | 1.6.0 | 1.6.0 |
msm Multi-State Markov and Hidden Markov Models in Continuous Time | 1.7 | 1.7 |
msmtools Building Augmented Data to Run Multi-State Models with 'msm' Package | 2.0.1 | 2.0.1 |
msos Data Sets and Functions Used in Multivariate Statistics: Old School by John Marden | 1.2.0 | 1.2.0 |
msSurv Nonparametric Estimation for Multistate Models | 1.2-2 | 1.2-2 |
MST Multivariate Survival Trees | 2.2 | 2.2 |
mstate Data Preparation, Estimation and Prediction in Multi-State Models | 0.3.2 | 0.3.2 |
MSwM Fitting Markov Switching Models | 1.5 | 1.5 |
MTS All-Purpose Toolkit for Analyzing Multivariate Time Series (MTS) and Estimating Multivariate Volatility Models | 1.2.1 | 1.2.1 |
mtsdi Multivariate Time Series Data Imputation | 0.3.5 | 0.3.5 |
mudfold Multiple UniDimensional unFOLDing | 1.1.21 | 1.1.21 |
muhaz Hazard Function Estimation in Survival Analysis | 1.2.6.4 | 1.2.6.4 |
multcomp Simultaneous Inference in General Parametric Models | 1.4-23 | 1.4-23 |
multcompView Visualizations of Paired Comparisons | 0.1-8 | 0.1-8 |
multDM Multivariate Version of the Diebold-Mariano Test | 1.1.4 | 1.1.4 |
multgee GEE Solver for Correlated Nominal or Ordinal Multinomial Responses | 1.8.0 | 1.8.0 |
multicool Permutations of Multisets in Cool-Lex Order | 0.1-12 | 0.1-12 |
MultiFit Multiscale Fisher's Independence Test for Multivariate Dependence | 1.1.1 | 1.1.1 |
MultiLCIRT Multidimensional Latent Class Item Response Theory Models | 2.11 | 2.11 |
multilevel Multilevel Functions | 2.7 | 2.7 |
MultiMeta Meta-analysis of Multivariate Genome Wide Association Studies | 0.1 | 0.1 |
multinomRob Robust Estimation of Overdispersed Multinomial Regression Models | 1.8-6.1 | 1.8-6.1 |
MultipleBubbles Test and Detection of Explosive Behaviors for Time Series | 0.2.0 | 0.2.0 |
multipleNCC Weighted Cox-Regression for Nested Case-Control Data | 1.2-2 | 1.2-2 |
multiplex Algebraic Tools for the Analysis of Multiple Social Networks | 2.9.9 | 2.9.9 |
multipol Multivariate Polynomials | 1.0-7 | 1.0-7 |
MultiRNG Multivariate Pseudo-Random Number Generation | 1.2.4 | 1.2.4 |
multiROC Calculating and Visualizing ROC and PR Curves Across Multi-Class Classifications | 1.1.1 | 1.1.1 |
multitaper Spectral Analysis Tools using the Multitaper Method | 1.0-15 | 1.0-15 |
multiway Component Models for Multi-Way Data | 1.0-6 | 1.0-6 |
multiwayvcov Multi-Way Standard Error Clustering | 1.2.3 | 1.2.3 |
multtest Resampling-based multiple hypothesis testing | 2.52.0 | 2.52.0 |
MuMIn Multi-Model Inference | 1.47.5 | 1.47.5 |
munfold Metric Unfolding | 0.3.5 | 0.3.5 |
munsell Utilities for Using Munsell Colours | 0.5.0 | 0.5.0 |
musica Multiscale Climate Model Assessment | 0.1.3 | 0.1.3 |
mutoss Unified Multiple Testing Procedures | 0.1-13 | 0.1-13 |
mvLSW Multivariate, Locally Stationary Wavelet Process Estimation | 1.2.5 | 1.2.5 |
mvmesh Multivariate Meshes and Histograms in Arbitrary Dimensions | 1.6 | 1.6 |
mvmeta Multivariate and Univariate Meta-Analysis and Meta-Regression | 1.0.3 | 1.0.3 |
mvMORPH Multivariate Comparative Tools for Fitting Evolutionary Models to Morphometric Data | 1.1.7 | 1.1.7 |
mvna Nelson-Aalen Estimator of the Cumulative Hazard in Multistate Models | 2.0.1 | 2.0.1 |
mvnfast Fast Multivariate Normal and Student's t Methods | 0.2.8 | 0.2.8 |
mvnmle ML Estimation for Multivariate Normal Data with Missing Values | 0.1-11.1 | 0.1-11.1 |
mvnormtest Normality test for multivariate variables | 0.1-9 | 0.1-9 |
mvoutlier Multivariate Outlier Detection Based on Robust Methods | 2.1.1 | 2.1.1 |
mvp Fast Symbolic Multivariate Polynomials | 1.0-12 | 1.0-12 |
mvprpb Orthant Probability of the Multivariate Normal Distribution | 1.0.4 | 1.0.4 |
mvQuad Methods for Multivariate Quadrature | 1.0-6 | 1.0-6 |
mvrtn Mean and Variance of Truncated Normal Distribution | 1.0 | 1.0 |
mvtmeta Multivariate Meta-Analysis | 1.1 | 1.1 |
mvtnorm Multivariate Normal and t Distributions | 1.1-3 | 1.1-3 |
mvtsplot Multivariate Time Series Plot | 1.0-1 | 1.0-1 |
n1qn1 Port of the 'Scilab' 'n1qn1' Module for Unconstrained BFGS Optimization | 6.0.1-11 | 6.0.1-11 |
nabor Wraps 'libnabo', a Fast K Nearest Neighbour Library for Low Dimensions | 0.5.0 | 0.5.0 |
NADA Nondetects and Data Analysis for Environmental Data | 1.6-1.1 | 1.6-1.1 |
NAEPirtparams IRT Parameters for the National Assessment of Education Progress | 1.0.0 | 1.0.0 |
NAEPprimer The NAEP Primer | 1.0.1 | 1.0.1 |
naivebayes High Performance Implementation of the Naive Bayes Algorithm | 0.9.7 | 0.9.7 |
naniar Data Structures, Summaries, and Visualisations for Missing Data | 1.0.0 | 1.0.0 |
nardl Nonlinear Cointegrating Autoregressive Distributed Lag Model | 0.1.6 | 0.1.6 |
narray Subset- And Name-Aware Array Utility Functions | 0.5.1 | 0.5.1 |
nasapower NASA POWER API Client | 4.0.10 | 4.0.10 |
natserv 'NatureServe' Interface | 1.0.0 | 1.0.0 |
natural Estimating the Error Variance in a High-Dimensional Linear Model | 0.9.0 | 0.9.0 |
naturalsort Natural Ordering | 0.1.3 | 0.1.3 |
NbClust Determining the Best Number of Clusters in a Data Set | 3.0.1 | 3.0.1 |
ncappc NCA Calculations and Population Model Diagnosis | 0.3.0 | 0.3.0 |
ncar Noncompartmental Analysis for Pharmacokinetic Report | 0.4.5 | 0.4.5 |
ncbit Retrieve and Build NBCI Taxonomic Data | 2013.03.29.1 | 2013.03.29.1 |
ncdf.tools Easier 'NetCDF' File Handling | 0.7.1.295 | 0.7.1.295 |
ncdf4 Interface to Unidata netCDF (Version 4 or Earlier) Format Data Files | 1.19 | 1.19 |
ncdfgeom 'NetCDF' Geometry and Time Series | 1.1.1 | 1.1.1 |
nCDunnett Noncentral Dunnett's Test Distribution | 1.1.0 | 1.1.0 |
ncf Spatial Covariance Functions | 1.3-2 | 1.3-2 |
ncmeta Straightforward 'NetCDF' Metadata | 0.3.5 | 0.3.5 |
nCopula Hierarchical Archimedean Copulas Constructed with Multivariate Compound Distributions | 0.1.1 | 0.1.1 |
ncvreg Regularization Paths for SCAD and MCP Penalized Regression Models | 3.13.0 | 3.13.0 |
ndjson Wicked-Fast Streaming 'JSON' ('ndjson') Reader | 0.9.0 | 0.9.0 |
ndtv Network Dynamic Temporal Visualizations | 0.13.2 | 0.13.2 |
neldermead R Port of the 'Scilab' Neldermead Module | 1.0-12 | 1.0-12 |
NestedCohort Survival Analysis for Cohorts with Missing Covariate Information | 1.1-3 | 1.1-3 |
netmeta Network Meta-Analysis using Frequentist Methods | 2.8-1 | 2.8-1 |
netrankr Analyzing Partial Rankings in Networks | 1.1.1 | 1.1.1 |
nets Network Estimation for Time Series | 0.9.1 | 0.9.1 |
netSEM Network Structural Equation Modeling | 0.5.1 | 0.5.1 |
network Classes for Relational Data | 1.18.1 | 1.18.1 |
NetworkChange Bayesian Package for Network Changepoint Analysis | 0.8 | 0.8 |
networkD3 D3 JavaScript Network Graphs from R | 0.4 | 0.4 |
networkDynamic Dynamic Extensions for Network Objects | 0.11.2 | 0.11.2 |
networkLite An Simplified Implementation of the 'network' Package Functionality | 1.0.5 | 1.0.5 |
NetworkRiskMeasures Risk Measures for (Financial) Networks | 0.1.4 | 0.1.4 |
NetworkToolbox Methods and Measures for Brain, Cognitive, and Psychometric Network Analysis | 1.4.2 | 1.4.2 |
networktools Tools for Identifying Important Nodes in Networks | 1.5.0 | 1.5.0 |
networktree Recursive Partitioning of Network Models | 1.0.1 | 1.0.1 |
neuralnet Training of Neural Networks | 1.44.2 | 1.44.2 |
NeuralNetTools Visualization and Analysis Tools for Neural Networks | 1.5.3 | 1.5.3 |
neurobase 'Neuroconductor' Base Package with Helper Functions for 'nifti' Objects | 1.32.3 | 1.32.3 |
neuroim Data Structures and Handling for Neuroimaging Data | 0.0.6 | 0.0.6 |
neuRosim Simulate fMRI Data | 0.2-13 | 0.2-13 |
Newdistns Computes Pdf, Cdf, Quantile and Random Numbers, Measures of Inference for 19 General Families of Distributions | 2.1 | 2.1 |
nFactors Parallel Analysis and Other Non Graphical Solutions to the Cattell Scree Test | 2.4.1.1 | 2.4.1.1 |
ngram Fast n-Gram 'Tokenization' | 3.2.1 | 3.2.1 |
ngramrr A Simple General Purpose N-Gram Tokenizer | 0.2.0 | 0.2.0 |
ngspatial Fitting the Centered Autologistic and Sparse Spatial Generalized Linear Mixed Models for Areal Data | 1.2-2 | 1.2-2 |
NGSSEML Non-Gaussian State-Space with Exact Marginal Likelihood | 2.2 | 2.2 |
nhdR Tools for Working with the National Hydrography Dataset | 0.5.9 | 0.5.9 |
NHPoisson Modelling and Validation of Non Homogeneous Poisson Processes | 3.3 | 3.3 |
nilde Nonnegative Integer Solutions of Linear Diophantine Equations with Applications | 1.1-7 | 1.1-7 |
nimble MCMC, Particle Filtering, and Programmable Hierarchical Modeling | 0.13.0 | 0.13.0 |
nipals Principal Components Analysis using NIPALS or Weighted EMPCA, with Gram-Schmidt Orthogonalization | 0.8 | 0.8 |
NISTunits Fundamental Physical Constants and Unit Conversions from NIST | 1.0.1 | 1.0.1 |
NlcOptim Solve Nonlinear Optimization with Nonlinear Constraints | 0.6 | 0.6 |
nleqslv Solve Systems of Nonlinear Equations | 3.3.4 | 3.3.4 |
NlinTS Models for Non Linear Causality Detection in Time Series | 1.4.5 | 1.4.5 |
nlist Lists of Numeric Atomic Objects | 0.3.3 | 0.3.3 |
nlme Linear and Nonlinear Mixed Effects Models | 3.1-162 | 3.1-162 |
nlmeODE Non-linear mixed-effects modelling in nlme using differential equations | 1.1 | 1.1 |
nlmixr Nonlinear Mixed Effects Models in Population PK/PD | 2.0.7 | 2.0.7 |
nlmrt Functions for Nonlinear Least Squares Solutions | 2016.3.2 | 2016.3.2 |
nloptr R Interface to NLopt | 2.0.3 | 2.0.3 |
NLP Natural Language Processing Infrastructure | 0.2-1 | 0.2-1 |
nlreg Higher Order Inference for Nonlinear Heteroscedastic Models | 1.2-2.2 | 1.2-2.2 |
nls2 Non-Linear Regression with Brute Force | 0.3-3 | 0.3-3 |
nlsem Fitting Structural Equation Mixture Models | 0.8 | 0.8 |
nlsr Functions for Nonlinear Least Squares Solutions - Updated 2022 | 2023.2.12 | 2023.2.12 |
nlstools Tools for Nonlinear Regression Analysis | 2.0-0 | 2.0-0 |
nlts Nonlinear Time Series Analysis | 1.0-2 | 1.0-2 |
nmadb Network Meta-Analysis Database API | 1.2.0 | 1.2.0 |
NMADiagT Network Meta-Analysis of Multiple Diagnostic Tests | 0.1.2 | 0.1.2 |
nmaINLA Network Meta-Analysis using Integrated Nested Laplace Approximations | 1.1.0 | 1.1.0 |
NMAoutlier Detecting Outliers in Network Meta-Analysis | 0.1.18 | 0.1.18 |
nmathresh Thresholds and Invariant Intervals for Network Meta-Analysis | 0.1.6 | 0.1.6 |
NMF Algorithms and Framework for Nonnegative Matrix Factorization (NMF) | 0.25 | 0.25 |
NMOF Numerical Methods and Optimization in Finance | 2.7-1 | 2.7-1 |
nmw Understanding Nonlinear Mixed Effects Modeling for Population Pharmacokinetics | 0.1.4 | 0.1.4 |
nnet Feed-Forward Neural Networks and Multinomial Log-Linear Models | 7.3-18 | 7.3-18 |
nnfor Time Series Forecasting with Neural Networks | 0.9.6 | 0.9.6 |
nnls The Lawson-Hanson algorithm for non-negative least squares<U+000a>(NNLS) | 1.4 | 1.4 |
nnTensor Non-Negative Tensor Decomposition | 1.1.6 | 1.1.6 |
nomisr Access 'Nomis' UK Labour Market Data | 0.4.6 | 0.4.6 |
NonCompart Noncompartmental Analysis for Pharmacokinetic Data | 0.6.0 | 0.6.0 |
nonlinearTseries Nonlinear Time Series Analysis | 0.2.12 | 0.2.12 |
nonneg.cg Non-Negative Conjugate-Gradient Minimizer | 0.1.6-1 | 0.1.6-1 |
nor1mix Normal aka Gaussian (1-d) Mixture Models (S3 Classes and Methods) | 1.3-0 | 1.3-0 |
norm Analysis of Multivariate Normal Datasets with Missing Values | 1.0-10.0 | 1.0-10.0 |
NormalGamma Normal-gamma convolution model | 1.1 | 1.1 |
NormalLaplace The Normal Laplace Distribution | 0.3-0 | 0.3-0 |
normalp Routines for Exponential Power Distribution | 0.7.2 | 0.7.2 |
NORMT3 Evaluates Complex Erf, Erfc, Faddeeva, and Density of Sum of Gaussian and Student's t | 1.0-3 | 1.0-3 |
nortest Tests for Normality | 1.0-4 | 1.0-4 |
notifyme Send Alerts to your Cellphone and Phillips Hue Lights | 0.3.0 | 0.3.0 |
Nozzle.R1 Nozzle Reports | 1.1-1.1 | 1.1-1.1 |
np Nonparametric Kernel Smoothing Methods for Mixed Data Types | 0.60-17 | 0.60-17 |
nparACT Non-Parametric Measures of Actigraphy Data | 0.8 | 0.8 |
NPBayesImputeCat Non-Parametric Bayesian Multiple Imputation for Categorical Data | 0.4 | 0.4 |
npde Normalised Prediction Distribution Errors for Nonlinear Mixed-Effect Models | 3.2 | 3.2 |
NPflow Bayesian Nonparametrics for Automatic Gating of Flow-Cytometry Data | 0.13.3 | 0.13.3 |
NPHMC Sample Size Calculation for the Proportional Hazards Mixture Cure Model | 2.3 | 2.3 |
NPMLEcmprsk Type-Specific Failure Rate and Hazard Rate on Competing Risks Data | 3.0 | 3.0 |
nppbib Nonparametric Partially-Balanced Incomplete Block Design Analysis | 1.2-0 | 1.2-0 |
npst Generalization of Hewitt's Seasonality Test | 2.0 | 2.0 |
npsurv Nonparametric Survival Analysis | 0.5-0 | 0.5-0 |
nsarfima Methods for Fitting and Simulating Non-Stationary ARFIMA Models | 0.2.0.0 | 0.2.0.0 |
nse Numerical Standard Errors Computation in R | 1.21 | 1.21 |
NSM3 Functions and Datasets to Accompany Hollander, Wolfe, and Chicken - Nonparametric Statistical Methods, Third Edition | 1.16 | 1.16 |
nsprcomp Non-Negative and Sparse PCA | 0.5.1-2 | 0.5.1-2 |
nsRFA Non-Supervised Regional Frequency Analysis | 0.7-15 | 0.7-15 |
nsyllable Count Syllables in Character Vectors | 1.0.1 | 1.0.1 |
NTS Nonlinear Time Series Analysis | 1.1.2 | 1.1.2 |
nullabor Tools for Graphical Inference | 0.3.9 | 0.3.9 |
numbers Number-Theoretic Functions | 0.8-5 | 0.8-5 |
numDeriv Accurate Numerical Derivatives | 2016.8-1.1 | 2016.8-1.1 |
nvmix Multivariate Normal Variance Mixtures | 0.1-0 | 0.1-0 |
nws R functions for NetWorkSpaces and Sleigh | 1.7.0.1 | 1.7.0.1 |
nycflights13 Flights that Departed NYC in 2013 | 1.0.2 | 1.0.2 |
oai General Purpose 'Oai-PMH' Services Client | 0.4.0 | 0.4.0 |
OAIHarvester Harvest Metadata Using OAI-PMH Version 2.0 | 0.3-4 | 0.3-4 |
Oarray Arrays with Arbitrary Offsets | 1.4-9 | 1.4-9 |
obAnalytics Limit Order Book Analytics | 0.1.1 | 0.1.1 |
occ Estimates PET Neuroreceptor Occupancies | 1.1 | 1.1 |
oce Analysis of Oceanographic Data | 1.7-10 | 1.7-10 |
odbc Connect to ODBC Compatible Databases (using the DBI Interface) | 1.3.4 | 1.3.4 |
odeintr C++ ODE Solvers Compiled on-Demand | 1.7.1 | 1.7.1 |
odpc One-Sided Dynamic Principal Components | 2.0.5 | 2.0.5 |
OECD Search and Extract Data from the OECD | 0.2.5 | 0.2.5 |
officer Manipulation of Microsoft Word and PowerPoint Documents | 0.6.0 | 0.6.0 |
ofGEM A Meta-Analysis Approach with Filtering for Identifying Gene-Level Gene-Environment Interactions with Genetic Association Data | 1.0 | 1.0 |
oligo | 1.60.0 | 1.60.0 |
oligoClasses | 1.58.0 | 1.58.0 |
olsrr Tools for Building OLS Regression Models | 0.5.3 | 0.5.3 |
ompr Model and Solve Mixed Integer Linear Programs | 1.0.3 | 1.0.3 |
OneR One Rule Machine Learning Classification Algorithm with Enhancements | 2.2 | 2.2 |
onion Octonions and Quaternions | 1.5-0 | 1.5-0 |
onlineVAR Online Fitting of Time-Adaptive Lasso Vector Auto Regression | 0.1-1 | 0.1-1 |
onls Orthogonal Nonlinear Least-Squares Regression | 0.1-2 | 0.1-2 |
onnx R Interface to 'ONNX' | 0.0.3 | 0.0.3 |
ooplah Helper Functions for Class Object-Oriented Programming | 0.2.0 | 0.2.0 |
OOR Optimistic Optimization in R | 0.1.3 | 0.1.3 |
openadds Client to Access 'Openaddresses' Data | 0.2.0 | 0.2.0 |
openair Tools for the Analysis of Air Pollution Data | 2.16-0 | 2.16-0 |
opencage Geocode with the OpenCage API | 0.2.2 | 0.2.2 |
opencpu Producing and Reproducing Results | 2.2.9 | 2.2.9 |
openEBGM EBGM Disproportionality Scores for Adverse Event Data Mining | 0.8.3 | 0.8.3 |
openintro Data Sets and Supplemental Functions from 'OpenIntro' Textbooks and Labs | 2.4.0 | 2.4.0 |
OpenML Open Machine Learning and Open Data Platform | 1.12 | 1.12 |
OpenMx Extended Structural Equation Modelling | 2.20.6 | 2.20.6 |
openNLP Apache OpenNLP Tools Interface | 0.2-7 | 0.2-7 |
openNLPdata Apache OpenNLP Jars and Basic English Language Models | 1.5.3-4 | 1.5.3-4 |
openssl Toolkit for Encryption, Signatures and Certificates Based on OpenSSL | 2.0.0 | 2.0.0 |
openSTARS An Open Source Implementation of the 'ArcGIS' Toolbox 'STARS' | 1.2.3 | 1.2.3 |
OpenStreetMap Access to Open Street Map Raster Images | 0.3.4 | 0.3.4 |
opentraj Tools for Creating and Analysing Air Trajectory Data | 1.0 | 1.0 |
openxlsx Read, Write and Edit xlsx Files | 4.2.5.2 | 4.2.5.2 |
operator.tools Utilities for Working with R's Operators | 1.6.3 | 1.6.3 |
operators Additional Binary Operators | 0.1-8 | 0.1-8 |
optextras Tools to Support Optimization Possibly with Bounds and Masks | 2019-12.4 | 2019-12.4 |
OptHedging Estimation of value and hedging strategy of call and put options. | 1.0 | 1.0 |
OptimaRegion Confidence Regions for Optima of Response Surfaces | 1.2 | 1.2 |
optimbase R Port of the 'Scilab' Optimbase Module | 1.0-10 | 1.0-10 |
optimParallel Parallel Version of the L-BFGS-B Optimization Method | 1.0-2 | 1.0-2 |
optimsimplex R Port of the 'Scilab' Optimsimplex Module | 1.0-8 | 1.0-8 |
optimx Expanded Replacement and Extension of the 'optim' Function | 2022-4.30 | 2022-4.30 |
OptionPricing Option Pricing with Efficient Simulation Algorithms | 0.1.1 | 0.1.1 |
optiscale Optimal Scaling | 1.2.2 | 1.2.2 |
optiSolve Linear, Quadratic, and Rational Optimization | 1.0 | 1.0 |
optmatch Functions for Optimal Matching | 0.10.0 | 0.10.0 |
optparse Command Line Option Parser | 1.7.1 | 1.7.1 |
optR Optimization Toolbox for Solving Linear Systems | 1.2.5 | 1.2.5 |
opusminer OPUS Miner Algorithm for Filtered Top-k Association Discovery | 0.1-1 | 0.1-1 |
OpVaR Statistical Methods for Modelling Operational Risk | 1.2 | 1.2 |
ORDER2PARENT Estimate parent distributions with data of several order statistics | 1.0 | 1.0 |
OrdFacReg Least Squares, Logistic, and Cox-Regression with Ordered Predictors | 1.0.6 | 1.0.6 |
ordinal Regression Models for Ordinal Data | 2022.11-16 | 2022.11-16 |
OrdNor Concurrent Generation of Ordinal and Normal Data with Given Correlation Matrix and Marginal Distributions | 2.2.3 | 2.2.3 |
ore An R Interface to the Onigmo Regular Expression Library | 1.7.3.1 | 1.7.3.1 |
org.At.tair.db | 3.15.1 | 3.15.1 |
org.Hs.eg.db | 3.14.0 | 3.14.0 |
OrgMassSpecR Organic Mass Spectrometry | 0.5-3 | 0.5-3 |
ORIClust Order-Restricted Information Criterion-Based Clustering Algorithm | 1.0-2 | 1.0-2 |
orloca Operations Research LOCational Analysis Models | 4.10 | 4.10 |
oro.dicom Rigorous - DICOM Input / Output | 0.5.3 | 0.5.3 |
oro.nifti Rigorous - 'NIfTI' + 'ANALYZE' + 'AFNI' : Input / Output | 0.11.4 | 0.11.4 |
orthogonalsplinebasis Orthogonal B-Spline Basis Functions | 0.1.7 | 0.1.7 |
OrthoPanels Dynamic Panel Models with Orthogonal Reparameterization of Fixed Effects | 1.2-4 | 1.2-4 |
orthopolynom Collection of Functions for Orthogonal and Orthonormal Polynomials | 1.0-6.1 | 1.0-6.1 |
osmar OpenStreetMap and R | 1.1-7 | 1.1-7 |
osmdata Import 'OpenStreetMap' Data as Simple Features or Spatial Objects | 0.2.1 | 0.2.1 |
osmplotr Bespoke Images of 'OpenStreetMap' Data | 0.3.3 | 0.3.3 |
osqp Quadratic Programming Solver using the 'OSQP' Library | 0.6.0.8 | 0.6.0.8 |
osrm Interface Between R and the OpenStreetMap-Based Routing Service OSRM | 3.5.1 | 3.5.1 |
otrimle Robust Model-Based Clustering | 2.0 | 2.0 |
otsad Online Time Series Anomaly Detectors | 0.2.0 | 0.2.0 |
ouch Ornstein-Uhlenbeck Models for Phylogenetic Comparative Hypotheses | 2.18 | 2.18 |
outbreaker Bayesian Reconstruction of Disease Outbreaks by Combining Epidemiologic and Genomic Data | 1.1-8 | 1.1-8 |
OutlierDC Outlier Detection using quantile regression for Censored Data | 0.3-0 | 0.3-0 |
OutlierDM Outlier Detection for Multi-replicated High-throughput Data | 1.1.1 | 1.1.1 |
outliers Tests for Outliers | 0.15 | 0.15 |
OUwie Analysis of Evolutionary Rates in an OU Framework | 2.10 | 2.10 |
overlapping Estimation of Overlapping in Empirical Distributions | 2.0 | 2.0 |
OwenQ Owen Q-Function | 1.0.6 | 1.0.6 |
owmr OpenWeatherMap API Wrapper | 0.8.2 | 0.8.2 |
ows4R Interface to OGC Web-Services (OWS) | 0.2-1 | 0.2-1 |
p3state.msm Analyzing Survival Data from an Illness-Death Model | 1.3 | 1.3 |
pa Performance Attribution for Equity Portfolios | 1.2-2 | 1.2-2 |
pacbpred PAC-Bayesian Estimation and Prediction in Sparse Additive Models. | 0.92.2 | 0.92.2 |
pack Convert values to/from raw vectors | 0.1-1 | 0.1-1 |
packcircles Circle Packing | 0.3.5 | 0.3.5 |
packrat A Dependency Management System for Projects and their R Package Dependencies | 0.9.1 | 0.9.1 |
Pade Padé Approximant Coefficients | 1.0.5 | 1.0.5 |
padr Quickly Get Datetime Data Ready for Analysis | 0.6.2 | 0.6.2 |
paf Attributable Fraction Function for Censored Survival Data | 1.0 | 1.0 |
PAFit Generative Mechanism Estimation in Temporal Complex Networks | 1.2.5 | 1.2.5 |
pagedown Paginate the HTML Output of R Markdown with CSS for Print | 0.18 | 0.18 |
pageviews An API Client for Wikimedia Traffic Data | 0.5.0 | 0.5.0 |
PairedData Paired Data Analysis | 1.1.1 | 1.1.1 |
pairwise Rasch Model Parameters by Pairwise Algorithm | 0.6.0-0 | 0.6.0-0 |
paleotree Paleontological and Phylogenetic Analyses of Evolution | 3.4.5 | 3.4.5 |
paleoTS Analyze Paleontological Time-Series | 0.5.3 | 0.5.3 |
palmerpenguins Palmer Archipelago (Antarctica) Penguin Data | 0.1.1 | 0.1.1 |
palmtree Partially Additive (Generalized) Linear Model Trees | 0.9-1 | 0.9-1 |
pampe Implementation of the Panel Data Approach Method for Program Evaluation | 1.1.2 | 1.1.2 |
pamr Pam: Prediction Analysis for Microarrays | 1.56.1 | 1.56.1 |
pan Multiple Imputation for Multivariate Panel or Clustered Data | 1.6 | 1.6 |
pander An R 'Pandoc' Writer | 0.6.5 | 0.6.5 |
panelaggregation Aggregate Longitudinal Survey Data | 0.1.1 | 0.1.1 |
panelAR Estimation of Linear AR(1) Panel Data Models with Cross-Sectional Heteroskedasticity and/or Correlation | 0.1 | 0.1 |
Paneldata Linear models for panel data | 1.0 | 1.0 |
panelr Regression Models and Utilities for Repeated Measures and Panel Data | 0.7.6 | 0.7.6 |
panelvar Panel Vector Autoregression | 0.5.5 | 0.5.5 |
papeR A Toolbox for Writing Pretty Papers and Reports | 1.0-5 | 1.0-5 |
paradox Define and Work with Parameter Spaces for Complex Algorithms | 0.11.1 | 0.11.1 |
parallel | 4.2.3 | 4.2.3 |
parallelly Enhancing the 'parallel' Package | 1.35.0 | 1.35.0 |
parallelMap Unified Interface to Parallelization Back-Ends | 1.5.1 | 1.5.1 |
param6 A Fast and Lightweight R6 Parameter Interface | 0.2.4 | 0.2.4 |
parameters Processing of Model Parameters | 0.17.0 | 0.17.0 |
ParamHelpers Helpers for Parameters in Black-Box Optimization, Tuning and Machine Learning | 1.14.1 | 1.14.1 |
params Simplify Parameters | 0.7.3 | 0.7.3 |
paran Horn's Test of Principal Components/Factors | 1.5.2 | 1.5.2 |
parcor Regularized estimation of partial correlation matrices | 0.2-6 | 0.2-6 |
ParetoPosStable Computing, Fitting and Validating the PPS Distribution | 1.1 | 1.1 |
parfm Parametric Frailty Models | 2.7.6 | 2.7.6 |
parma Portfolio Allocation and Risk Management Applications | 1.7 | 1.7 |
parmigene Parallel Mutual Information Estimation for Gene Network Reconstruction | 1.1.0 | 1.1.0 |
parsedate Recognize and Parse Dates in Various Formats, Including All ISO 8601 Formats | 1.3.1 | 1.3.1 |
parSim Parallel Simulation Studies | 0.1.4 | 0.1.4 |
parsnip A Common API to Modeling and Analysis Functions | 0.2.1 | 0.2.1 |
partDSA Partitioning Using Deletion, Substitution, and Addition Moves | 0.9.14 | 0.9.14 |
partitions Additive Partitions of Integers | 1.10-4 | 1.10-4 |
partools Tools for the 'Parallel' Package | 1.1.6 | 1.1.6 |
partsm Periodic Autoregressive Time Series Models | 1.1-3 | 1.1-3 |
party A Laboratory for Recursive Partytioning | 1.3-13 | 1.3-13 |
partykit A Toolkit for Recursive Partytioning | 1.2-18 | 1.2-18 |
pastecs Package for Analysis of Space-Time Ecological Series | 1.3.21 | 1.3.21 |
pastis Phylogenetic Assembly with Soft Taxonomic Inferences | 0.1-2 | 0.1-2 |
patchDVI Package to Patch '.dvi' or '.synctex' Files | 1.10.1 | 1.10.1 |
patchSynctex Communication Between Editor and Viewer for Literate Programs | 0.1-4 | 0.1-4 |
patchwork The Composer of Plots | 1.1.2 | 1.1.2 |
pawacc Physical Activity with Accelerometers | 1.2.2 | 1.2.2 |
PAWL Implementation of the PAWL algorithm | 0.5 | 0.5 |
paws Amazon Web Services Software Development Kit | 0.2.0 | 0.2.0 |
paws.analytics 'Amazon Web Services' Analytics Services | 0.2.0 | 0.2.0 |
paws.application.integration 'Amazon Web Services' Application Integration Services | 0.2.0 | 0.2.0 |
paws.common Paws Low-Level Amazon Web Services API | 0.5.6 | 0.5.6 |
paws.compute 'Amazon Web Services' Compute Services | 0.2.0 | 0.2.0 |
paws.cost.management 'Amazon Web Services' Cost Management Services | 0.2.0 | 0.2.0 |
paws.customer.engagement 'Amazon Web Services' Customer Engagement Services | 0.2.0 | 0.2.0 |
paws.database 'Amazon Web Services' Database Services | 0.2.0 | 0.2.0 |
paws.developer.tools 'Amazon Web Services' Developer Tools Services | 0.2.0 | 0.2.0 |
paws.end.user.computing 'Amazon Web Services' End User Computing Services | 0.2.0 | 0.2.0 |
paws.machine.learning 'Amazon Web Services' Machine Learning Services | 0.2.0 | 0.2.0 |
paws.management 'Amazon Web Services' Management & Governance Services | 0.2.0 | 0.2.0 |
paws.networking 'Amazon Web Services' Networking & Content Delivery Services | 0.2.0 | 0.2.0 |
paws.security.identity 'Amazon Web Services' Security, Identity, & Compliance Services | 0.2.0 | 0.2.0 |
paws.storage 'Amazon Web Services' Storage Services | 0.2.0 | 0.2.0 |
pbapply Adding Progress Bar to '*apply' Functions | 1.7-0 | 1.7-0 |
pbatR Pedigree/Family-Based Genetic Association Tests Analysis and Power | 2.2-13 | 2.2-13 |
PBD Protracted Birth-Death Model of Diversification | 1.4 | 1.4 |
pbdMPI Programming with Big Data -- Interface to MPI | 0.4-6 | 0.4-6 |
pbdNCDF4 Programming with Big Data -- Interface to Parallel Unidata<U+000a>NetCDF4 Format Data Files | 0.1-4 | 0.1-4 |
pbdPROF Programming with Big Data -- MPI Profiling Tools | 0.4-0 | 0.4-0 |
pbdSLAP Programming with Big Data -- Scalable Linear Algebra Packages | 0.3-2 | 0.3-2 |
pbdZMQ Programming with Big Data -- Interface to 'ZeroMQ' | 0.3-7 | 0.3-7 |
pbivnorm Vectorized Bivariate Normal CDF | 0.6.0 | 0.6.0 |
pbkrtest Parametric Bootstrap, Kenward-Roger and Satterthwaite Based Methods for Test in Mixed Models | 0.5.2 | 0.5.2 |
pbmcapply Tracking the Progress of Mc*pply with Progress Bar | 1.5.1 | 1.5.1 |
pbo Probability of Backtest Overfitting | 1.3.5 | 1.3.5 |
pbs Periodic B Splines | 1.1 | 1.1 |
PBSddesolve Solver for Delay Differential Equations | 1.13.3 | 1.13.3 |
PBSmapping Mapping Fisheries Data and Spatial Analysis Tools | 2.73.2 | 2.73.2 |
PBSmodelling GUI Tools Made Easy: Interact with Models and Explore Data | 2.68.8 | 2.68.8 |
pbv Probabilities for Bivariate Normal Distribution | 0.4-22 | 0.4-22 |
PCA4TS Segmenting Multiple Time Series by Contemporaneous Linear Transformation | 0.1 | 0.1 |
pcalg Methods for Graphical Models and Causal Inference | 2.7-7 | 2.7-7 |
pcaMethods | 1.88.0 | 1.88.0 |
pcaPP Robust PCA by Projection Pursuit | 2.0-3 | 2.0-3 |
pcdpca Dynamic Principal Components for Periodically Correlated Functional Time Series | 0.4 | 0.4 |
pch Piecewise Constant Hazard Models for Censored and Truncated Data | 2.0 | 2.0 |
pchc Bayesian Network Learning with the PCHC and Related Algorithms | 0.8 | 0.8 |
PCICt Implementation of POSIXct Work-Alike for 365 and 360 Day Calendars | 0.5-4.4 | 0.5-4.4 |
pcIRT IRT Models for Polytomous and Continuous Item Responses | 0.2.4 | 0.2.4 |
PCMRS Model Response Styles in Partial Credit Models | 0.1-4 | 0.1-4 |
pcnetmeta Patient-Centered Network Meta-Analysis | 2.8 | 2.8 |
pco Panel Cointegration Tests | 1.0.1 | 1.0.1 |
PCPS Principal Coordinates of Phylogenetic Structure | 1.0.7 | 1.0.7 |
pcse Panel-Corrected Standard Error Estimation in R | 1.9.1.1 | 1.9.1.1 |
pct Propensity to Cycle Tool | 0.9.3 | 0.9.3 |
pcts Periodically Correlated and Periodically Integrated Time Series | 0.15.5 | 0.15.5 |
pd.hg.u133.plus.2 | 3.12.0 | 3.12.0 |
pd.hg18.60mer.expr | 3.12.0 | 3.12.0 |
pd.hugene.2.0.st | 3.14.1 | 3.14.1 |
pd.mogene.2.1.st | 3.14.1 | 3.14.1 |
pd.mouse430.2 | 3.12.0 | 3.12.0 |
pd.mta.1.0 | 3.12.0 | 3.12.0 |
pd.porcine | 3.12.0 | 3.12.0 |
pdc Permutation Distribution Clustering | 1.0.3 | 1.0.3 |
pder Panel Data Econometrics with R | 1.0-2 | 1.0-2 |
pdfCluster Cluster Analysis via Nonparametric Density Estimation | 1.0-4 | 1.0-4 |
pdfetch Fetch Economic and Financial Time Series Data from Public Sources | 0.2.8 | 0.2.8 |
pdftables Programmatic Conversion of PDF Tables | 0.1 | 0.1 |
pdftools Text Extraction, Rendering and Converting of PDF Documents | 3.3.3 | 3.3.3 |
pdist Partitioned Distance Function | 1.2.1 | 1.2.1 |
pdp Partial Dependence Plots | 0.8.1 | 0.8.1 |
PDQutils PDQ Functions via Gram Charlier, Edgeworth, and Cornish Fisher Approximations | 0.1.6 | 0.1.6 |
pdR Threshold Model and Unit Root Tests in Cross-Section and Time Series Data | 1.8 | 1.8 |
pear Package for Periodic Autoregression Analysis | 1.2 | 1.2 |
PearsonDS Pearson Distribution System | 1.2.3 | 1.2.3 |
PearsonICA Independent Component Analysis using Score Functions from the Pearson System | 1.2-5 | 1.2-5 |
pec Prediction Error Curves for Risk Prediction Models in Survival Analysis | 2022.05.04 | 2022.05.04 |
pedigree Pedigree Functions | 1.4.2 | 1.4.2 |
pedometrics Miscellaneous Pedometric Tools | 0.12.1 | 0.12.1 |
PeerPerformance Luck-Corrected Peer Performance Analysis in R | 2.2.5 | 2.2.5 |
pegas Population and Evolutionary Genetics Analysis System | 1.1 | 1.1 |
penalized L1 (Lasso and Fused Lasso) and L2 (Ridge) Penalized Estimation in GLMs and in the Cox Model | 0.9-52 | 0.9-52 |
penalizedLDA Penalized Classification using Fisher's Linear Discriminant | 1.1 | 1.1 |
PenCoxFrail Regularization in Cox Frailty Models | 1.0.1 | 1.0.1 |
pendensity Density Estimation with a Penalized Mixture Approach | 0.2.13 | 0.2.13 |
penMSM Estimating Regularized Multi-state Models Using L1 Penalties | 0.99 | 0.99 |
peperr Parallelised Estimation of Prediction Error | 1.4 | 1.4 |
perARMA Periodic Time Series Analysis | 1.6 | 1.6 |
performance Assessment of Regression Models Performance | 0.10.2 | 0.10.2 |
PerformanceAnalytics Econometric Tools for Performance and Risk Analysis | 2.0.4 | 2.0.4 |
perm Exact or Asymptotic Permutation Tests | 1.0-0.2 | 1.0-0.2 |
PermAlgo Permutational Algorithm to Simulate Survival Data | 1.2 | 1.2 |
permutations The Symmetric Group: Permutations of a Finite Set | 1.1-2 | 1.1-2 |
permute Functions for Generating Restricted Permutations of Data | 0.9-7 | 0.9-7 |
perry Resampling-Based Prediction Error Estimation for Regression Models | 0.3.1 | 0.3.1 |
perturb Tools for Evaluating Collinearity | 2.10 | 2.10 |
pgirmess Spatial Analysis and Data Mining for Field Ecologists | 1.7.0 | 1.7.0 |
pglm Panel Generalized Linear Models | 0.2-3 | 0.2-3 |
pgmm Parsimonious Gaussian Mixture Models | 1.2.5 | 1.2.5 |
phangorn Phylogenetic Reconstruction and Analysis | 2.11.1 | 2.11.1 |
PharmPow Pharmacometric Power calculations for mixed study designs | 1.0 | 1.0 |
pheatmap Pretty Heatmaps | 1.0.12 | 1.0.12 |
PHEindicatormethods Common Public Health Statistics and their Confidence Intervals | 1.3.2 | 1.3.2 |
PHeval Evaluation of the Proportional Hazards Assumption with a Standardized Score Process | 0.5.4 | 0.5.4 |
philentropy Similarity and Distance Quantification Between Probability Functions | 0.7.0 | 0.7.0 |
phonics Phonetic Spelling Algorithms | 1.3.10 | 1.3.10 |
phonTools Tools for Phonetic and Acoustic Analyses | 0.2-2.1 | 0.2-2.1 |
photobiology Photobiological Calculations | 0.10.10 | 0.10.10 |
photobiologyFilters Spectral Transmittance and Spectral Reflectance Data | 0.5.2 | 0.5.2 |
photobiologyWavebands Waveband Definitions for UV, VIS, and IR Radiation | 0.4.5 | 0.4.5 |
phyclust Phylogenetic Clustering (Phyloclustering) | 0.1-33 | 0.1-33 |
phyext2 An Extension (for Package 'SigTree') of Some of the Classes in Package 'phylobase' | 0.0.4 | 0.0.4 |
phylin Spatial Interpolation of Genetic Data | 2.0.2 | 2.0.2 |
phylobase Base Package for Phylogenetic Structures and Comparative Data | 0.8.10 | 0.8.10 |
phylocanvas Interactive Phylogenetic Trees Using the 'Phylocanvas' JavaScript Library | 0.1.3 | 0.1.3 |
phyloclim Integrating Phylogenetics and Climatic Niche Modeling | 0.9.5 | 0.9.5 |
phylocomr Interface to 'Phylocom' | 0.3.3 | 0.3.3 |
PHYLOGR Functions for Phylogenetically Based Statistical Analyses | 1.0.11 | 1.0.11 |
phylogram Dendrograms for Evolutionary Analysis | 2.1.0 | 2.1.0 |
phyloland Modelling Competitive Exclusion and Limited Dispersal in a Statistical Phylogeographic Framework | 1.3 | 1.3 |
phylolm Phylogenetic Linear Regression | 2.6.2 | 2.6.2 |
phyloseq | 1.40.0 | 1.40.0 |
phylotate Phylogenies with Annotations | 1.3 | 1.3 |
phylotools Phylogenetic Tools for Eco-Phylogenetics | 0.2.2 | 0.2.2 |
phyloTop Calculating Topological Properties of Phylogenies | 2.1.2 | 2.1.2 |
phyreg The Phylogenetic Regression of Grafen (1989) | 1.0.2 | 1.0.2 |
PhysicalActivity Process Accelerometer Data for Physical Activity Measurement | 0.2-4 | 0.2-4 |
phytools Phylogenetic Tools for Comparative Biology (and Other Things) | 1.5-1 | 1.5-1 |
picante Integrating Phylogenies and Ecology | 1.8.2 | 1.8.2 |
picasso Pathwise Calibrated Sparse Shooting Algorithm | 1.3.1 | 1.3.1 |
piecewiseSEM Piecewise Structural Equation Modeling | 2.3.0 | 2.3.0 |
pillar Coloured Formatting for Columns | 1.8.1 | 1.8.1 |
pimeta Prediction Intervals for Random-Effects Meta-Analysis | 1.1.3 | 1.1.3 |
pinbasic Fast and Stable Estimation of the Probability of Informed Trading (PIN) | 1.2.2 | 1.2.2 |
pingr Check if a Remote Computer is Up | 2.0.2 | 2.0.2 |
PIPS Predicted Interval Plots | 1.0.1 | 1.0.1 |
pivotaltrackR A Client for the 'Pivotal Tracker' API | 0.2.0 | 0.2.0 |
pixmap Bitmap Images / Pixel Maps | 0.4-12 | 0.4-12 |
pkgbuild Find Tools Needed to Build R Packages | 1.4.0 | 1.4.0 |
pkgcache Cache 'CRAN'-Like Metadata and R Packages | 2.0.4 | 2.0.4 |
pkgconfig Private Configuration for 'R' Packages | 2.0.3 | 2.0.3 |
pkgdepends Package Dependency Resolution and Downloads | 0.4.0 | 0.4.0 |
pkgdown Make Static HTML Documentation for a Package | 2.0.3 | 2.0.3 |
pkgKitten Create Simple Packages Which Do not Upset R Package Checks | 0.2.2 | 0.2.2 |
pkgload Simulate Package Installation and Attach | 1.3.1 | 1.3.1 |
pkgnet Get Network Representation of an R Package | 0.4.2 | 0.4.2 |
PKgraph Model diagnostics for population pharmacokinetic models | 1.7 | 1.7 |
pkgsearch Search and Query CRAN R Packages | 3.1.2 | 3.1.2 |
PKNCA Perform Pharmacokinetic Non-Compartmental Analysis | 0.10.1 | 0.10.1 |
PKPDmodels Pharmacokinetic/pharmacodynamic models | 0.3.2 | 0.3.2 |
pkr Pharmacokinetics in R | 0.1.3 | 0.1.3 |
PKreport A reporting pipeline for checking population pharmacokinetic model assumption | 1.5 | 1.5 |
pks Probabilistic Knowledge Structures | 0.5-0 | 0.5-0 |
plac A Pairwise Likelihood Augmented Cox Estimator for Left-Truncated Data | 0.1.1 | 0.1.1 |
PlackettLuce Plackett-Luce Models for Rankings | 0.4.2 | 0.4.2 |
plainview Plot Raster Images Interactively on a Plain HTML Canvas | 0.1.0 | 0.1.0 |
planar Multilayer Optics | 1.6 | 1.6 |
plm Linear Models for Panel Data | 2.6-1 | 2.6-1 |
PLMIX Bayesian Analysis of Finite Mixtures of Plackett-Luce Models for Partial Rankings/Orderings | 2.1.1 | 2.1.1 |
PLmixed Estimate (Generalized) Linear Mixed Models with Factor Structures | 0.1.6 | 0.1.6 |
plogr The 'plog' C++ Logging Library | 0.2.0 | 0.2.0 |
plot3D Plotting Multi-Dimensional Data | 1.4 | 1.4 |
plot3Drgl Plotting Multi-Dimensional Data - Using 'rgl' | 1.0.2 | 1.0.2 |
plotdap Easily Visualize Data from 'ERDDAP' Servers via the 'rerddap' Package | 1.0.1 | 1.0.1 |
plotKML Visualization of Spatial and Spatio-Temporal Objects in Google Earth | 0.8-3 | 0.8-3 |
plotly Create Interactive Web Graphics via 'plotly.js' | 4.10.1 | 4.10.1 |
plotMCMC MCMC Diagnostic Plots | 2.0.1 | 2.0.1 |
plotmo Plot a Model's Residuals, Response, and Partial Dependence Plots | 3.6.2 | 3.6.2 |
plotrix Various Plotting Functions | 3.8-2 | 3.8-2 |
plotSEMM Graphing Nonlinear Relations Among Latent Variables from Structural Equation Mixture Models | 2.4 | 2.4 |
plRasch Log Linear by Linear Association models and Rasch family models by pseudolikelihood estimation | 1.0 | 1.0 |
pls Partial Least Squares and Principal Component Regression | 2.8-1 | 2.8-1 |
plsdof Degrees of Freedom and Statistical Inference for Partial Least Squares Regression | 0.3-0 | 0.3-0 |
plsgenomics PLS Analyses for Genomics | 1.5-2 | 1.5-2 |
plspm Partial Least Squares Path Modeling (PLS-PM) | 0.4.9 | 0.4.9 |
plsRbeta Partial Least Squares Regression for Beta Regression Models | 0.3.0 | 0.3.0 |
plsRglm Partial Least Squares Regression for Generalized Linear Models | 1.5.1 | 1.5.1 |
plumber An API Generator for R | 1.2.1 | 1.2.1 |
plusser A Google+ Interface for R | 0.4-0 | 0.4-0 |
plyr Tools for Splitting, Applying and Combining Data | 1.8.8 | 1.8.8 |
pmc Phylogenetic Monte Carlo | 1.0.4 | 1.0.4 |
pmclust Parallel Model-Based Clustering using Expectation-Gathering-Maximization Algorithm for Finite Mixture Gaussian Model | 0.2-1 | 0.2-1 |
PMCMRplus Calculate Pairwise Multiple Comparisons of Mean Rank Sums Extended | 1.9.4 | 1.9.4 |
pmml Generate PMML for Various Models | 2.5.2 | 2.5.2 |
pmmlTransformations Transforms Input Data from a PMML Perspective | 1.3.3 | 1.3.3 |
pmr Probability Models for Ranking Data | 1.2.5.1 | 1.2.5.1 |
pmultinom One-Sided Multinomial Probabilities | 1.0.0 | 1.0.0 |
pmxTools Pharmacometric and Pharmacokinetic Toolkit | 1.3 | 1.3 |
png Read and write PNG images | 0.1-7 | 0.1-7 |
poibin The Poisson Binomial Distribution | 1.5 | 1.5 |
PoiClaClu Classification and Clustering of Sequencing Data Based on a Poisson Model | 1.0.2.1 | 1.0.2.1 |
poilog Poisson Lognormal and Bivariate Poisson Lognormal Distribution | 0.4.2 | 0.4.2 |
pointblank Data Validation and Organization of Metadata for Local and Remote Tables | 0.11.3 | 0.11.3 |
poisbinom A Faster Implementation of the Poisson-Binomial Distribution | 1.0.1 | 1.0.1 |
poistweedie Poisson-Tweedie Exponential Family Models | 1.0.1 | 1.0.1 |
poLCA Polytomous Variable Latent Class Analysis | 1.6.0.1 | 1.6.0.1 |
polspline Polynomial Spline Routines | 1.1.22 | 1.1.22 |
polyaAeppli Implementation of the Polya-Aeppli Distribution | 2.0.2 | 2.0.2 |
polyclip Polygon Clipping | 1.10-4 | 1.10-4 |
polycor Polychoric and Polyserial Correlations | 0.8-1 | 0.8-1 |
polyCub Cubature over Polygonal Domains | 0.8.1 | 0.8.1 |
polynom A Collection of Functions to Implement a Class for Univariate Polynomial Manipulations | 1.4-1 | 1.4-1 |
PolynomF Polynomials in R | 2.0-5 | 2.0-5 |
polyreg Polynomial Regression | 0.8.0 | 0.8.0 |
polysat Tools for Polyploid Microsatellite Analysis | 1.7-6 | 1.7-6 |
pomp Statistical Inference for Partially Observed Markov Processes | 4.7 | 4.7 |
pool Object Pooling | 1.0.1 | 1.0.1 |
poolr Methods for Pooling P-Values from (Dependent) Tests | 1.1-1 | 1.1-1 |
poorman A Poor Man's Dependency Free Recreation of 'dplyr' | 0.2.5 | 0.2.5 |
popbio Construction and Analysis of Matrix Population Models | 2.7 | 2.7 |
PopED Population (and Individual) Optimal Experimental Design | 0.6.0 | 0.6.0 |
poppr Genetic Analysis of Populations with Mixed Reproduction | 2.9.3 | 2.9.3 |
portfolio Analysing Equity Portfolios | 0.5-2 | 0.5-2 |
PortfolioEffectHFT High Frequency Portfolio Analytics by PortfolioEffect | 1.8 | 1.8 |
PortfolioOptim Small/Large Sample Portfolio Optimization | 1.1.1 | 1.1.1 |
portfolioSim Framework for simulating equity portfolio strategies | 0.2-7 | 0.2-7 |
PortRisk Portfolio Risk Analysis | 1.1.0 | 1.1.0 |
posterior Tools for Working with Posterior Distributions | 1.2.1 | 1.2.1 |
postGIStools Tools for Interacting with 'PostgreSQL' / 'PostGIS' Databases | 0.2.4 | 0.2.4 |
postlightmercury Parses Web Pages using Postlight Mercury | 1.2 | 1.2 |
POT Generalized Pareto Distribution and Peaks Over Threshold | 1.1-10 | 1.1-10 |
PottsUtils Utility Functions of the Potts Models | 0.3-3 | 0.3-3 |
powdist Power and Reversal Power Distributions | 0.1.4 | 0.1.4 |
poweRlaw Analysis of Heavy Tailed Distributions | 0.70.6 | 0.70.6 |
powerlmm Power Analysis for Longitudinal Multilevel Models | 0.4.0 | 0.4.0 |
powerSurvEpi Power and Sample Size Calculation for Survival Analysis of Epidemiological Studies | 0.1.3 | 0.1.3 |
PowerTOST Power and Sample Size for (Bio)Equivalence Studies | 1.5-4 | 1.5-4 |
PP Person Parameter Estimation | 0.6.3-11 | 0.6.3-11 |
ppcor Partial and Semi-Partial (Part) Correlation | 1.1 | 1.1 |
ppls Penalized Partial Least Squares | 1.6-1.1 | 1.6-1.1 |
pps PPS Sampling | 1.0 | 1.0 |
prabclus Functions for Clustering and Testing of Presence-Absence, Abundance and Multilocus Genetic Data | 2.3-2 | 2.3-2 |
pracma Practical Numerical Math Functions | 2.3.8 | 2.3.8 |
PracTools Tools for Designing and Weighting Survey Samples | 1.2.8 | 1.2.8 |
praise Praise Users | 1.0.0 | 1.0.0 |
prcr Person-Centered Analysis | 0.2.1 | 0.2.1 |
PreciseSums Accurate Floating Point Sums and Products | 0.5 | 0.5 |
prediction Tidy, Type-Safe 'prediction()' Methods | 0.3.14 | 0.3.14 |
predmixcor Classification rule based on Bayesian mixture models with feature selection bias corrected | 1.1-1 | 1.1-1 |
prefmod Utilities to Fit Paired Comparison Models for Preferences | 0.8-35 | 0.8-35 |
PReMiuM Dirichlet Process Bayesian Clustering, Profile Regression | 3.2.7 | 3.2.7 |
preprocessCore | 1.58.0 | 1.58.0 |
PresenceAbsence Presence-Absence Model Evaluation | 1.1.10 | 1.1.10 |
prettycode Pretty Print R Code in the Terminal | 1.1.0 | 1.1.0 |
prettydoc Creating Pretty Documents from R Markdown | 0.4.1 | 0.4.1 |
prettyGraphs Publication-Quality Graphics | 2.1.6 | 2.1.6 |
prettymapr Scale Bar, North Arrow, and Pretty Margins in R | 0.2.3 | 0.2.3 |
prettyR Pretty Descriptive Stats | 2.2-3 | 2.2-3 |
prettyunits Pretty, Human Readable Formatting of Quantities | 1.1.1 | 1.1.1 |
prevalence Tools for Prevalence Assessment Studies | 0.4.1 | 0.4.1 |
prevR Estimating Regional Trends of a Prevalence from a DHS and Similar Surveys | 4.0.1 | 4.0.1 |
prim Patient Rule Induction Method (PRIM) | 1.0.20 | 1.0.20 |
primefactr Use Prime Factorization for Computations | 0.1.1 | 0.1.1 |
primePCA Projected Refinement for Imputation of Missing Entries in PCA | 1.2 | 1.2 |
primes Fast Functions for Prime Numbers | 1.4.0 | 1.4.0 |
PRIMME Eigenvalues and Singular Values and Vectors from Large Matrices | 3.2-3 | 3.2-3 |
princurve Fit a Principal Curve in Arbitrary Dimension | 2.1.6 | 2.1.6 |
PRISMAstatement Plot Flow Charts According to the "PRISMA" Statement | 1.1.1 | 1.1.1 |
probhat Multivariate Generalized Kernel Smoothing and Related Statistical Methods | 0.4.1 | 0.4.1 |
ProbitSpatial Probit with Spatial Dependence, SAR, SEM and SARAR Models | 1.1 | 1.1 |
pROC Display and Analyze ROC Curves | 1.18.0 | 1.18.0 |
processx Execute and Control System Processes | 3.8.0 | 3.8.0 |
prodigenr Research Project Directory Generator | 0.6.2 | 0.6.2 |
prodlim Product-Limit Estimation for Censored Event History Analysis | 2019.11.13 | 2019.11.13 |
ProfessR Grades Setting and Exam Maker | 2.4-1 | 2.4-1 |
profileModel Profiling Inference Functions for Various Model Classes | 0.6.1 | 0.6.1 |
profileR Profile Analysis of Multivariate Data in R | 0.3-5 | 0.3-5 |
profmem Simple Memory Profiling for R | 0.6.0 | 0.6.0 |
profr An Alternative Display for Profiling Information | 0.3.3 | 0.3.3 |
proftools Profile Output Processing Tools for R | 0.99-3 | 0.99-3 |
profvis Interactive Visualizations for Profiling R Code | 0.3.7 | 0.3.7 |
progress Terminal Progress Bars | 1.2.2 | 1.2.2 |
progressr An Inclusive, Unifying API for Progress Updates | 0.10.0 | 0.10.0 |
PROJ Generic Coordinate System Transformations Using 'PROJ' | 0.4.0 | 0.4.0 |
proj4 A simple interface to the PROJ.4 cartographic projections library | 1.0-11 | 1.0-11 |
projects A Project Infrastructure for Researchers | 2.1.3 | 2.1.3 |
ProjectTemplate Automates the Creation of New Statistical Analysis Projects | 0.10.3 | 0.10.3 |
promises Abstractions for Promise-Based Asynchronous Programming | 1.2.0.1 | 1.2.0.1 |
PropClust Propensity Clustering and Decomposition | 1.4-6 | 1.4-6 |
prophet Automatic Forecasting Procedure | 1.0 | 1.0 |
propr Calculating Proportionality Between Vectors of Compositional Data | 4.2.6 | 4.2.6 |
ProtGenerics | 1.28.0 | 1.28.0 |
proto Prototype Object-Based Programming | 1.0.0 | 1.0.0 |
protoclust Hierarchical Clustering with Prototypes | 1.6.4 | 1.6.4 |
protolite Highly Optimized Protocol Buffer Serializers | 2.2.0 | 2.2.0 |
proxy Distance and Similarity Measures | 0.4-27 | 0.4-27 |
proxyC Computes Proximity in Large Sparse Matrices | 0.2.4 | 0.2.4 |
prrd Parallel Runs of Reverse Depends | 0.0.5 | 0.0.5 |
PRROC Precision-Recall and ROC Curves for Weighted and Unweighted Data | 1.3.1 | 1.3.1 |
pryr Tools for Computing on the Language | 0.1.6 | 0.1.6 |
ps List, Query, Manipulate System Processes | 1.7.3 | 1.7.3 |
PSAgraphics Propensity Score Analysis Graphics | 2.1.1 | 2.1.1 |
psbcGroup Penalized Parametric and Semiparametric Bayesian Survival Models with Shrinkage and Grouping Priors | 1.5 | 1.5 |
pscl Political Science Computational Laboratory | 1.5.5 | 1.5.5 |
psd Adaptive, Sine-Multitaper Power Spectral Density and Cross Spectrum Estimation | 2.1.1 | 2.1.1 |
pseudo Computes Pseudo-Observations for Modeling | 1.4.3 | 1.4.3 |
pseval Methods for Evaluating Principal Surrogates of Treatment Response | 1.3.1 | 1.3.1 |
PSF Forecasting of Univariate Time Series Using the Pattern Sequence-Based Forecasting (PSF) Algorithm | 0.5 | 0.5 |
psfmi Prediction Model Pooling, Selection and Performance Evaluation Across Multiply Imputed Datasets | 1.1.0 | 1.1.0 |
psgp Projected Spatial Gaussian Process Methods | 0.3-19 | 0.3-19 |
psidR Build Panel Data Sets from PSID Raw Data | 2.1 | 2.1 |
PSIMEX SIMEX Algorithm on Pedigree Structures | 1.1 | 1.1 |
pso Particle Swarm Optimization | 1.0.4 | 1.0.4 |
psoptim Particle Swarm Optimization | 1.0 | 1.0 |
pspline Penalized Smoothing Splines | 1.0-19 | 1.0-19 |
PST Probabilistic Suffix Trees and Variable Length Markov Chains | 0.94 | 0.94 |
psy Various Procedures Used in Psychometrics | 1.2 | 1.2 |
psych Procedures for Psychological, Psychometric, and Personality Research | 2.3.3 | 2.3.3 |
psychmeta Psychometric Meta-Analysis Toolkit | 2.6.5 | 2.6.5 |
psychometric Applied Psychometric Theory | 2.2 | 2.2 |
psychomix Psychometric Mixture Models | 1.1-8 | 1.1-8 |
psychonetrics Structural Equation Modeling and Confirmatory Network Analysis | 0.10 | 0.10 |
psychotools Psychometric Modeling Infrastructure | 0.7-2 | 0.7-2 |
psychotree Recursive Partitioning Based on Psychometric Models | 0.16-0 | 0.16-0 |
psyphy Functions for Analyzing Psychophysical Data in R | 0.2-3 | 0.2-3 |
PTAk Principal Tensor Analysis on k Modes | 2.0.0 | 2.0.0 |
ptsuite Tail Index Estimation for Power Law Distributions | 1.0.0 | 1.0.0 |
ptw Parametric Time Warping | 1.9-16 | 1.9-16 |
PubBias Performs simulation study to look for publication bias, using a technique described by Ioannidis and Trikalinos; Clin Trials. 2007;4(3):245-53. | 1.0 | 1.0 |
pubh A Toolbox for Public Health and Epidemiology | 1.2.7 | 1.2.7 |
PublicationBias Sensitivity Analysis for Publication Bias in Meta-Analyses | 2.3.0 | 2.3.0 |
Publish Format Output of Various Routines in a Suitable Way for Reports and Publication | 2023.01.17 | 2023.01.17 |
pubmed.mineR Text Mining of PubMed Abstracts | 1.0.19 | 1.0.19 |
pubmedR Gathering Metadata About Publications, Grants, Clinical Trials from 'PubMed' Database | 0.0.3 | 0.0.3 |
puma | 3.30.0 | 3.30.0 |
pumadata | 2.32.0 | 2.32.0 |
puniform Meta-Analysis Methods Correcting for Publication Bias | 0.2.5 | 0.2.5 |
purrr Functional Programming Tools | 1.0.1 | 1.0.1 |
purrrlyr Tools at the Intersection of 'purrr' and 'dplyr' | 0.0.8 | 0.0.8 |
pushoverr Send Push Notifications using 'Pushover' | 1.1.0 | 1.1.0 |
pvclust Hierarchical Clustering with P-Values via Multiscale Bootstrap Resampling | 2.2-0 | 2.2-0 |
pwr Basic Functions for Power Analysis | 1.3-0 | 1.3-0 |
pwrRasch Statistical Power Simulation for Testing the Rasch Model | 0.1-2 | 0.1-2 |
pwt Penn World Table (Versions 5.6, 6.x, 7.x) | 7.1-1 | 7.1-1 |
pwt8 Penn World Table (Version 8.x) | 8.1-1 | 8.1-1 |
pwt9 Penn World Table (Version 9.x) | 9.1-0 | 9.1-0 |
pxR PC-Axis with R | 0.42.4 | 0.42.4 |
pxweb R Interface to PXWEB APIs | 0.13.1 | 0.13.1 |
PxWebApiData PX-Web Data by API | 0.7.0 | 0.7.0 |
PythonInR Use 'Python' from Within 'R' | 0.1-12 | 0.1-12 |
qap Heuristics for the Quadratic Assignment Problem (QAP) | 0.1-2 | 0.1-2 |
qcv Quantifying Construct Validity | 1.0 | 1.0 |
qdap Bridging the Gap Between Qualitative Data and Quantitative Analysis | 2.4.3 | 2.4.3 |
qdapDictionaries Dictionaries and Word Lists for the 'qdap' Package | 1.0.7 | 1.0.7 |
qdapRegex Regular Expression Removal, Extraction, and Replacement Tools | 0.7.5 | 0.7.5 |
qdapTools Tools for the 'qdap' Package | 1.3.5 | 1.3.5 |
qgam Smooth Additive Quantile Regression Models | 1.3.4 | 1.3.4 |
qgraph Graph Plotting Methods, Psychometric Data Visualization and Graphical Model Estimation | 1.9.2 | 1.9.2 |
qmap Statistical Transformations for Post-Processing Climate Model Output | 1.0-4 | 1.0-4 |
qpdf Split, Combine and Compress PDF Files | 1.3.2 | 1.3.2 |
qqconf Creates Simultaneous Testing Bands for QQ-Plots | 1.2.3 | 1.2.3 |
qqman Q-Q and Manhattan Plots for GWAS Data | 0.1.8 | 0.1.8 |
qrandom True Random Numbers using the ANU Quantum Random Numbers Server | 1.2.4 | 1.2.4 |
QRM Provides R-Language Code to Examine Quantitative Risk Management Concepts | 0.4-31 | 0.4-31 |
qrmdata Data Sets for Quantitative Risk Management Practice | 2022-05-31-1 | 2022-05-31-1 |
qrmtools Tools for Quantitative Risk Management | 0.0-16 | 0.0-16 |
qrng (Randomized) Quasi-Random Number Generators | 0.0-8 | 0.0-8 |
qs Quick Serialization of R Objects | 0.25.5 | 0.25.5 |
qsub Running Commands Remotely on 'Gridengine' Clusters | 1.1.3 | 1.1.3 |
qtl Tools for Analyzing QTL Experiments | 1.58 | 1.58 |
qtlDesign Design of QTL experiments | 0.941 | 0.941 |
QTLRel Tools for Mapping of Quantitative Traits of Genetically Related Individuals and Calculating Identity Coefficients from Pedigrees | 1.12 | 1.12 |
Qtools Utilities for Quantiles | 1.5.6 | 1.5.6 |
quadprog Functions to Solve Quadratic Programming Problems | 1.5-8 | 1.5-8 |
quadprogXT Quadratic Programming with Absolute Value Constraints | 0.0.5 | 0.0.5 |
qualmap Opinionated Approach for Digitizing Semi-Structured Qualitative GIS Data | 0.2.0 | 0.2.0 |
qualtRics Download 'Qualtrics' Survey Data | 3.1.7 | 3.1.7 |
qualV Qualitative Validation Methods | 0.3-4 | 0.3-4 |
Quandl API Wrapper for Quandl.com | 2.11.0 | 2.11.0 |
quanteda Quantitative Analysis of Textual Data | 3.2.1 | 3.2.1 |
quanteda.textstats Textual Statistics for the Quantitative Analysis of Textual Data | 0.95 | 0.95 |
quantification Quantification of Qualitative Survey Data | 0.2.0 | 0.2.0 |
quantmod Quantitative Financial Modelling Framework | 0.4.20 | 0.4.20 |
QuantPsyc Quantitative Psychology Tools | 1.5 | 1.5 |
quantreg Quantile Regression | 5.93 | 5.93 |
quantregForest Quantile Regression Forests | 1.3-7 | 1.3-7 |
quantregGrowth Growth Charts via Smooth Regression Quantiles with Automatic Smoothness Estimation and Additive Terms | 1.4-0 | 1.4-0 |
quantstrat | 0.16.9 | 0.16.9 |
QuantTools Enhanced Quantitative Trading Modelling | 0.5.7.1 | 0.5.7.1 |
questionr Functions to Make Surveys Processing Easier | 0.7.8 | 0.7.8 |
QUIC Regularized Sparse Inverse Covariance Matrix Estimation | 1.1.1 | 1.1.1 |
quickmapr Quickly Map and Explore Spatial Data | 0.3.0 | 0.3.0 |
quickpsy Fits Psychometric Functions for Multiple Groups | 0.1.5.1 | 0.1.5.1 |
qvalue Q-value estimation for false discovery rate control | 2.28.0 | 2.28.0 |
qvcalc Quasi Variances for Factor Effects in Statistical Models | 1.0.2 | 1.0.2 |
QZ Generalized Eigenvalues and QZ Decomposition | 0.2-2 | 0.2-2 |
R.cache Fast and Light-Weight Caching (Memoization) of Objects and Results to Speed Up Computations | 0.15.0 | 0.15.0 |
R.matlab Read and Write MAT Files and Call MATLAB from Within R | 3.7.0 | 3.7.0 |
R.methodsS3 S3 Methods Simplified | 1.8.2 | 1.8.2 |
R.oo R Object-Oriented Programming with or without References | 1.25.0 | 1.25.0 |
R.rsp Dynamic Generation of Scientific Reports | 0.45.0 | 0.45.0 |
R.utils Various Programming Utilities | 2.12.2 | 2.12.2 |
R2admb 'ADMB' to R Interface Functions | 0.7.16.3 | 0.7.16.3 |
R2BayesX Estimate Structured Additive Regression Models with 'BayesX' | 1.1-1.1 | 1.1-1.1 |
r2d3 Interface to 'D3' Visualizations | 0.2.6 | 0.2.6 |
R2HTML HTML Exportation for R Objects | 2.3.3 | 2.3.3 |
R2jags Using R to Run 'JAGS' | 0.7-1 | 0.7-1 |
R2WinBUGS Running 'WinBUGS' and 'OpenBUGS' from 'R' / 'S-PLUS' | 2.1-21 | 2.1-21 |
R4CouchDB A R Convenience Layer for CouchDB 2.0 | 0.7.5 | 0.7.5 |
R6 Encapsulated Classes with Reference Semantics | 2.5.1 | 2.5.1 |
RaceID Identification of Cell Types and Inference of Lineage Trees from Single-Cell RNA-Seq Data | 0.2.3 | 0.2.3 |
radarchart Radar Chart from 'Chart.js' | 0.3.1 | 0.3.1 |
RadData Nuclear Decay Data for Dosimetric Calculations - ICRP 107 | 1.0.1 | 1.0.1 |
radiant Business Analytics using R and Shiny | 1.5.0 | 1.5.0 |
radiant.basics Basics Menu for Radiant: Business Analytics using R and Shiny | 1.5.0 | 1.5.0 |
radiant.data Data Menu for Radiant: Business Analytics using R and Shiny | 1.5.1 | 1.5.1 |
radiant.design Design Menu for Radiant: Business Analytics using R and Shiny | 1.5.0 | 1.5.0 |
radiant.model Model Menu for Radiant: Business Analytics using R and Shiny | 1.5.0 | 1.5.0 |
radiant.multivariate Multivariate Menu for Radiant: Business Analytics using R and Shiny | 1.5.0 | 1.5.0 |
radsafer Radiation Safety | 2.2.6 | 2.2.6 |
RAdwords Loading Google Adwords Data into R | 0.1.18 | 0.1.18 |
ragg Graphic Devices Based on AGG | 1.2.2 | 1.2.2 |
ragtop Pricing Equity Derivatives with Extensions of Black-Scholes | 1.1.1 | 1.1.1 |
rainbow Bagplots, Boxplots and Rainbow Plots for Functional Data | 3.6 | 3.6 |
ramcmc Robust Adaptive Metropolis Algorithm | 0.1.2 | 0.1.2 |
ramify Additional Matrix Functionality | 0.3.3 | 0.3.3 |
ramps Bayesian Geostatistical Modeling with RAMPS | 0.6.18 | 0.6.18 |
randaes Random number generator based on AES cipher | 0.3 | 0.3 |
RandMeta Efficient Numerical Algorithm for Exact Inference in Meta Analysis | 0.1.0 | 0.1.0 |
randNames Package Provides Access to Fake User Data | 0.2.3 | 0.2.3 |
random True Random Numbers using RANDOM.ORG | 0.2.6 | 0.2.6 |
RandomFields Simulation and Analysis of Random Fields | 3.3.14 | 3.3.14 |
RandomFieldsUtils Utilities for the Simulation and Analysis of Random Fields and Genetic Data | 1.2.5 | 1.2.5 |
randomForest Breiman and Cutler's Random Forests for Classification and Regression | 4.7-1.1 | 4.7-1.1 |
randomForestSRC Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC) | 3.1.0 | 3.1.0 |
randomGLM Random General Linear Model Prediction | 1.10-1 | 1.10-1 |
randomizr Easy-to-Use Tools for Common Forms of Random Assignment and Sampling | 0.22.0 | 0.22.0 |
randomLCA Random Effects Latent Class Analysis | 1.1-2 | 1.1-2 |
randtoolbox Toolbox for Pseudo and Quasi Random Number Generation and Random Generator Tests | 2.0.4 | 2.0.4 |
RandVar Implementation of Random Variables | 1.2.1 | 1.2.1 |
rangeMapper A Platform for the Study of Macro-Ecology of Life History Traits | 2.0.1 | 2.0.1 |
rangeModelMetadata Provides Templates for Metadata Files Associated with Species Range Models | 0.1.4 | 0.1.4 |
ranger A Fast Implementation of Random Forests | 0.14.1 | 0.14.1 |
rankdist Distance Based Ranking Models | 1.1.4 | 1.1.4 |
rankhazard Rank-Hazard Plots | 1.1.0 | 1.1.0 |
RANN Fast Nearest Neighbour Search (Wraps ANN Library) Using L2 Metric | 2.6.1 | 2.6.1 |
rapiclient Dynamic OpenAPI/Swagger Client | 0.1.3 | 0.1.3 |
rapidjsonr 'Rapidjson' C++ Header Files | 1.2.0 | 1.2.0 |
RApiSerialize R API Serialization | 0.1.2 | 0.1.2 |
rappdirs Application Directories: Determine Where to Save Data, Caches, and Logs | 0.3.3 | 0.3.3 |
rapport A Report Templating System | 1.1 | 1.1 |
rapportools Miscellaneous (Stats) Helper Functions with Sane Defaults for Reporting | 1.1 | 1.1 |
rARPACK Solvers for Large Scale Eigenvalue and SVD Problems | 0.11-0 | 0.11-0 |
RaschSampler Rasch Sampler | 0.8-8 | 0.8-8 |
raster Geographic Data Analysis and Modeling | 3.6-20 | 3.6-20 |
rasterImage An Improved Wrapper of image() | 0.4.0 | 0.4.0 |
rasterVis Visualization Methods for Raster Data | 0.51.5 | 0.51.5 |
ratelimitr Rate Limiting for R | 0.4.1 | 0.4.1 |
ratesci Confidence Intervals for Comparisons of Binomial or Poisson Rates | 0.4-0 | 0.4-0 |
rattle Graphical User Interface for Data Science in R | 5.5.1 | 5.5.1 |
rBayesianOptimization Bayesian Optimization of Hyperparameters | 1.2.0 | 1.2.0 |
Rbeast Bayesian Change-Point Detection and Time Series Decomposition | 0.9.3 | 0.9.3 |
rbenchmark Benchmarking routine for R | 1.0.0 | 1.0.0 |
RBGL An interface to the BOOST graph library | 1.72.0 | 1.72.0 |
rbibutils Read 'Bibtex' Files and Convert Between Bibliography Formats | 2.2.13 | 2.2.13 |
rbison Interface to the 'USGS' 'BISON' API | 1.0.0 | 1.0.0 |
Rbitcoin R & bitcoin integration | 0.9.2 | 0.9.2 |
Rblpapi R Interface to 'Bloomberg' | 0.3.13 | 0.3.13 |
rbokeh R Interface for Bokeh | 0.5.2 | 0.5.2 |
Rborist Extensible, Parallelizable Implementation of the Random Forest Algorithm | 0.3-2 | 0.3-2 |
RBtest Regression-Based Approach for Testing the Type of Missing Data | 1.1 | 1.1 |
rbundler Rbundler manages an application's dependencies systematically and repeatedly. | 0.3.7 | 0.3.7 |
Rcapture Loglinear Models for Capture-Recapture Experiments | 1.4-4 | 1.4-4 |
RCarb Dose Rate Modelling of Carbonate-Rich Samples | 0.1.5 | 0.1.5 |
RCassandra R/Cassandra interface | 0.1-3 | 0.1-3 |
rcdd Computational Geometry | 1.5 | 1.5 |
rcdk Interface to the 'CDK' Libraries | 3.7.0 | 3.7.0 |
rcdklibs The CDK Libraries Packaged for R | 2.8 | 2.8 |
RCEIM R Cross Entropy Inspired Method for Optimization | 0.3 | 0.3 |
Rcgmin Conjugate Gradient Minimization of Nonlinear Functions with Box Constraints | 2022-4.30 | 2022-4.30 |
rCMA R-to-Java Interface for 'CMA-ES' | 1.1.1 | 1.1.1 |
rcmdcheck Run 'R CMD check' from 'R' and Capture Results | 1.4.0 | 1.4.0 |
Rcmdr R Commander | 2.8-0 | 2.8-0 |
RcmdrMisc R Commander Miscellaneous Functions | 2.7-2 | 2.7-2 |
RcmdrPlugin.DoE R Commander Plugin for (Industrial) Design of Experiments | 0.12-4 | 0.12-4 |
RcmdrPlugin.EZR R Commander Plug-in for the EZR (Easy R) Package | 1.61 | 1.61 |
RcmdrPlugin.MA Graphical User Interface for Conducting Meta-Analyses in R | 0.0-2 | 0.0-2 |
RcmdrPlugin.RMTCJags R MTC Jags 'Rcmdr' Plugin | 1.0-2 | 1.0-2 |
RcmdrPlugin.sampling Tools for sampling in Official Statistical Surveys | 1.1 | 1.1 |
RcmdrPlugin.temis Graphical Integrated Text Mining Solution | 0.7.10 | 0.7.10 |
RColorBrewer ColorBrewer Palettes | 1.1-3 | 1.1-3 |
rcoreoa Client for the CORE API | 0.4.0 | 0.4.0 |
Rcpp Seamless R and C++ Integration | 1.0.10 | 1.0.10 |
RcppAlgos High Performance Tools for Combinatorics and Computational Mathematics | 2.7.2 | 2.7.2 |
RcppAnnoy 'Rcpp' Bindings for 'Annoy', a Library for Approximate Nearest Neighbors | 0.0.19 | 0.0.19 |
RcppArmadillo 'Rcpp' Integration for the 'Armadillo' Templated Linear Algebra Library | 0.12.0.1.0 | 0.12.0.1.0 |
RcppDE Global Optimization by Differential Evolution in C++ | 0.1.7 | 0.1.7 |
RcppDist 'Rcpp' Integration of Additional Probability Distributions | 0.1.1 | 0.1.1 |
RcppDL Deep Learning Methods via Rcpp | 0.0.5 | 0.0.5 |
RcppEigen 'Rcpp' Integration for the 'Eigen' Templated Linear Algebra Library | 0.3.3.9.3 | 0.3.3.9.3 |
RcppGSL 'Rcpp' Integration for 'GNU GSL' Vectors and Matrices | 0.3.11 | 0.3.11 |
RcppHNSW 'Rcpp' Bindings for 'hnswlib', a Library for Approximate Nearest Neighbors | 0.4.1 | 0.4.1 |
RcppNumerical 'Rcpp' Integration for Numerical Computing Libraries | 0.5-0 | 0.5-0 |
RcppParallel Parallel Programming Tools for 'Rcpp' | 5.1.7 | 5.1.7 |
RcppProgress An Interruptible Progress Bar with OpenMP Support for C++ in R Packages | 0.4.2 | 0.4.2 |
RcppQuantuccia R Bindings to the Calendaring Functionality of 'QuantLib' | 0.1.1 | 0.1.1 |
RcppRedis 'Rcpp' Bindings for 'Redis' using the 'hiredis' Library | 0.2.1 | 0.2.1 |
RcppRoll Efficient Rolling / Windowed Operations | 0.3.0 | 0.3.0 |
RcppSimdJson 'Rcpp' Bindings for the 'simdjson' Header-Only Library for 'JSON' Parsing | 0.1.9 | 0.1.9 |
RcppThread R-Friendly Threading in C++ | 2.1.3 | 2.1.3 |
RcppTOML 'Rcpp' Bindings to Parser for "Tom's Obvious Markup Language" | 0.2.2 | 0.2.2 |
RcppZiggurat 'Rcpp' Integration of Different "Ziggurat" Normal RNG Implementations | 0.1.6 | 0.1.6 |
Rcrawler Web Crawler and Scraper | 0.1.9-1 | 0.1.9-1 |
rcrossref Client for Various 'CrossRef' 'APIs' | 1.2.0 | 1.2.0 |
Rcsdp R Interface to the CSDP Semidefinite Programming Library | 0.1.57.4 | 0.1.57.4 |
RCurl General Network (HTTP/FTP/...) Client Interface for R | 1.98-1.10 | 1.98-1.10 |
rdatacite Client for the 'DataCite' API | 0.5.4 | 0.5.4 |
rdbnomics Download DBnomics Data | 0.6.4 | 0.6.4 |
rdd Regression Discontinuity Estimation | 0.57 | 0.57 |
rdetools Relevant Dimension Estimation (RDE) in Feature Spaces | 1.0 | 1.0 |
rdflib Tools to Manipulate and Query Semantic Data | 0.2.5 | 0.2.5 |
RDieHarder R Interface to the 'DieHarder' RNG Test Suite | 0.2.5 | 0.2.5 |
rdlocrand Local Randomization Methods for RD Designs | 1.0 | 1.0 |
rdmulti Analysis of RD Designs with Multiple Cutoffs or Scores | 1.0 | 1.0 |
Rdpack Update and Manipulate Rd Documentation Objects | 2.4 | 2.4 |
rdpla Client for the Digital Public Library of America ('DPLA') | 0.2.0 | 0.2.0 |
rdpower Power Calculations for RD Designs | 2.2 | 2.2 |
rdrobust Robust Data-Driven Statistical Inference in Regression-Discontinuity Designs | 2.1.0 | 2.1.0 |
rdrop2 Programmatic Interface to the 'Dropbox' API | 0.8.2.1 | 0.8.2.1 |
rdryad Access for Dryad Web Services | 1.0.0 | 1.0.0 |
Rdsdp R Interface to DSDP Semidefinite Programming Library | 1.0.5.2 | 1.0.5.2 |
Rdsm Threads Environment for R | 2.1.1 | 2.1.1 |
rdwd Select and Download Climate Data from 'DWD' (German Weather Service) | 1.6.0 | 1.6.0 |
re2 R Interface to Google RE2 (C++) Regular Expression Library | 0.1.2 | 0.1.2 |
reactable Interactive Data Tables for R | 0.4.4 | 0.4.4 |
reactR React Helpers | 0.4.4 | 0.4.4 |
ReacTran Reactive Transport Modelling in 1d, 2d and 3d | 1.4.3.1 | 1.4.3.1 |
read.gt3x Parse 'ActiGraph' 'GT3X'/'GT3X+' 'Accelerometer' Data | 1.2.0 | 1.2.0 |
readabs Download and Tidy Time Series Data from the Australian Bureau of Statistics | 0.4.13 | 0.4.13 |
readBrukerFlexData Reads Mass Spectrometry Data in Bruker *flex Format | 1.8.5 | 1.8.5 |
readJDX Import Data in the JCAMP-DX Format | 0.6.1 | 0.6.1 |
readMzXmlData Reads Mass Spectrometry Data in mzXML Format | 2.8.1 | 2.8.1 |
readODS Read and Write ODS Files | 1.8.0 | 1.8.0 |
readr Read Rectangular Text Data | 2.1.4 | 2.1.4 |
readsdmx Read SDMX-XML Data | 0.3.0 | 0.3.0 |
readstata13 Import 'Stata' Data Files | 0.10.1 | 0.10.1 |
readxl Read Excel Files | 1.4.2 | 1.4.2 |
rebird R Client for the eBird Database of Bird Observations | 1.3.0 | 1.3.0 |
rebmix Finite Mixture Modeling, Clustering & Classification | 2.14.2 | 2.14.2 |
recipes Preprocessing and Feature Engineering Steps for Modeling | 1.0.5 | 1.0.5 |
reclin Record Linkage Toolkit | 0.1.2 | 0.1.2 |
recmap Compute the Rectangular Statistical Cartogram | 1.0.11 | 1.0.11 |
recurse Computes Revisitation Metrics for Trajectory Data | 1.1.2 | 1.1.2 |
reda Recurrent Event Data Analysis | 0.5.4 | 0.5.4 |
redcapAPI Interface to 'REDCap' | 2.4.0 | 2.4.0 |
reddPrec Reconstruction of Daily Data - Precipitation | 0.4.0 | 0.4.0 |
redist Simulation Methods for Legislative Redistricting | 3.1.5 | 3.1.5 |
redland RDF Library Bindings in R | 1.0.17-16 | 1.0.17-16 |
redux R Bindings to 'hiredis' | 1.1.3 | 1.1.3 |
REEMtree Regression Trees with Random Effects for Longitudinal (Panel) Data | 0.90.4 | 0.90.4 |
RefManageR Straightforward 'BibTeX' and 'BibLaTeX' Bibliography Management | 1.4.0 | 1.4.0 |
refund Regression with Functional Data | 0.1-29 | 0.1-29 |
refund.shiny Interactive Plotting for Functional Data Analyses | 0.4.1 | 0.4.1 |
regions Processing Regional Statistics | 0.1.8 | 0.1.8 |
registr Curve Registration for Exponential Family Functional Data | 1.0.0 | 1.0.0 |
registry Infrastructure for R Package Registries | 0.5-1 | 0.5-1 |
regspec Non-Parametric Bayesian Spectrum Estimation for Multirate Data | 2.6 | 2.6 |
regtools Regression and Classification Tools | 1.7.0 | 1.7.0 |
reinforcelearn Reinforcement Learning | 0.2.1 | 0.2.1 |
ReIns Functions from "Reinsurance: Actuarial and Statistical Aspects" | 1.0.10 | 1.0.10 |
reinsureR Reinsurance Treaties Application | 0.1.0 | 0.1.0 |
rel Reliability Coefficients | 1.4.2 | 1.4.2 |
relations Data Structures and Algorithms for Relations | 0.6-13 | 0.6-13 |
relaxo Relaxed Lasso | 0.1-2 | 0.1-2 |
reldist Relative Distribution Methods | 1.7-0 | 1.7-0 |
reliaR Package for some probability distributions. | 0.01 | 0.01 |
relimp Relative Contribution of Effects in a Regression Model | 1.0-5 | 1.0-5 |
rematch Match Regular Expressions with a Nicer 'API' | 1.0.1 | 1.0.1 |
rematch2 Tidy Output from Regular Expression Matching | 2.1.2 | 2.1.2 |
remotes R Package Installation from Remote Repositories, Including 'GitHub' | 2.4.2 | 2.4.2 |
REndo Fitting Linear Models with Endogenous Regressors using Latent Instrumental Variables | 2.4.8 | 2.4.8 |
Renext Renewal Method for Extreme Values Extrapolation | 3.1-3 | 3.1-3 |
rentrez 'Entrez' in R | 1.2.3 | 1.2.3 |
renv Project Environments | 0.15.4 | 0.15.4 |
repmis Miscellaneous Tools for Reproducible Research | 0.5 | 0.5 |
repo A Data-Centered Data Flow Manager | 2.1.5 | 2.1.5 |
RepoGenerator Generates a Project and Repo for Easy Initialization of a Workshop | 0.0.1 | 0.0.1 |
reportr A General Message and Error Reporting System | 1.3.0 | 1.3.0 |
reporttools Generate "LaTeX"" Tables of Descriptive Statistics | 1.1.3 | 1.1.3 |
repr Serializable Representations | 1.1.4 | 1.1.4 |
represent Determine the representativity of two multidimensional data sets | 1.0 | 1.0 |
represtools Reproducible Research Tools | 0.1.3 | 0.1.3 |
reprex Prepare Reproducible Example Code via the Clipboard | 2.0.2 | 2.0.2 |
reproj Coordinate System Transformations for Generic Map Data | 0.4.3 | 0.4.3 |
reqres Powerful Classes for HTTP Requests and Responses | 0.2.5 | 0.2.5 |
REQS R/EQS Interface | 0.8-13 | 0.8-13 |
request High Level 'HTTP' Client | 0.1.0 | 0.1.0 |
rerddap General Purpose Client for 'ERDDAP' Servers | 1.0.2 | 1.0.2 |
rerddapXtracto Extracts Environmental Data from 'ERDDAP' Web Services | 1.1.4 | 1.1.4 |
resampledata Data Sets for Mathematical Statistics with Resampling in R | 0.3.1 | 0.3.1 |
resemble Memory-Based Learning in Spectral Chemometrics | 2.1.2 | 2.1.2 |
reservoir Tools for Analysis, Design, and Operation of Water Supply Storages | 1.1.5 | 1.1.5 |
reshape Flexibly Reshape Data | 0.8.9 | 0.8.9 |
reshape2 Flexibly Reshape Data: A Reboot of the Reshape Package | 1.4.4 | 1.4.4 |
ResourceSelection Resource Selection (Probability) Functions for Use-Availability Data | 0.3-5 | 0.3-5 |
restfulr R Interface to RESTful Web Services | 0.0.15 | 0.0.15 |
restimizeapi Functions for Working with the 'www.estimize.com' Web Services | 1.0.0 | 1.0.0 |
resumer Build Resumes with R | 0.0.5 | 0.0.5 |
reticulate Interface to 'Python' | 1.24 | 1.24 |
retimes Reaction Time Analysis | 0.1-2 | 0.1-2 |
revdbayes Ratio-of-Uniforms Sampling for Bayesian Extreme Value Analysis | 1.5.0 | 1.5.0 |
revealjs R Markdown Format for 'reveal.js' Presentations | 0.9 | 0.9 |
revtools Tools to Support Evidence Synthesis | 0.4.1 | 0.4.1 |
reweight Adjustment of Survey Respondent Weights | 1.2.1 | 1.2.1 |
rex Friendly Regular Expressions | 1.2.1 | 1.2.1 |
Rexperigen R Interface to Experigen | 0.2.1 | 0.2.1 |
Rfacebook Access to Facebook API via R | 0.6.15 | 0.6.15 |
Rfast A Collection of Efficient and Extremely Fast R Functions | 2.0.7 | 2.0.7 |
Rfast2 A Collection of Efficient and Extremely Fast R Functions II | 0.1.4 | 0.1.4 |
rfigshare An R Interface to 'figshare' | 0.3.8 | 0.3.8 |
Rfit Rank-Based Estimation for Linear Models | 0.24.2 | 0.24.2 |
RForcecom Data Integration Feature for Force.com and Salesforce.com | 1.1 | 1.1 |
RGA A Google Analytics API Client | 0.4.2 | 0.4.2 |
rgbif Interface to the Global Biodiversity Information Facility API | 3.7.5 | 3.7.5 |
rgdal Bindings for the 'Geospatial' Data Abstraction Library | 1.5-23 | 1.5-23 |
rgen Random Sampling Distribution C++ Routines for Armadillo | 0.0.1 | 0.0.1 |
RGENERATE Tools to Generate Vector Time Series | 1.3.7 | 1.3.7 |
rgenoud R Version of GENetic Optimization Using Derivatives | 5.9-0.3 | 5.9-0.3 |
rgeolocate IP Address Geolocation | 1.4.2 | 1.4.2 |
rgeos Interface to Geometry Engine - Open Source ('GEOS') | 0.5-9 | 0.5-9 |
RGF Regularized Greedy Forest | 1.1.1 | 1.1.1 |
rggobi Interface Between R and 'GGobi' | 2.1.22 | 2.1.22 |
rgl 3D Visualization Using OpenGL | 1.0.1 | 1.0.1 |
Rglpk R/GNU Linear Programming Kit Interface | 0.6-4 | 0.6-4 |
RGoogleFit R Interface to Google Fit API | 0.4.0 | 0.4.0 |
RgoogleMaps Overlays on Static Maps | 1.4.5.3 | 1.4.5.3 |
RGraphics Data and Functions from the Book R Graphics, Third Edition | 3.0-2 | 3.0-2 |
Rgraphviz Provides plotting capabilities for R graph objects | 2.26.0 | 2.26.0 |
rgrass7 Deprecated Interface Between GRASS Geographical Information System and R | 0.2-10 | 0.2-10 |
RGreenplum Interface to 'Greenplum' Database | 0.1.2 | 0.1.2 |
RGtk2 R Bindings for Gtk 2.8.0 and Above | 2.20.36.2 | 2.20.36.2 |
RH2 DBI/RJDBC Interface to H2 Database | 0.2.4 | 0.2.4 |
rhandsontable Interface to the 'Handsontable.js' Library | 0.3.8 | 0.3.8 |
rhdf5 | 2.40.0 | 2.40.0 |
rhdf5filters | 1.8.0 | 1.8.0 |
Rhdf5lib | 1.18.2 | 1.18.2 |
RHMS Hydrologic Modelling System for R Users | 1.7 | 1.7 |
rhosp Side Effect Risks in Hospital : Simulation and Estimation | 1.10 | 1.10 |
Rhpc Permits *apply() Style Dispatch for 'HPC' | 0.21-247 | 0.21-247 |
RhpcBLASctl Control the Number of Threads on 'BLAS' | 0.23-42 | 0.23-42 |
Rhtslib | 1.28.0 | 1.28.0 |
rhub Connect to 'R-hub' | 1.1.2 | 1.1.2 |
ridigbio Interface to the iDigBio Data API | 0.3.5 | 0.3.5 |
riingo An R Interface to the 'Tiingo' Stock Price API | 0.3.1 | 0.3.1 |
Rilostat ILO Open Data via Ilostat Bulk Download Facility or SDMX Web Service | 1.1.8 | 1.1.8 |
ring Circular / Ring Buffers | 1.0.3 | 1.0.3 |
RInside C++ Classes to Embed R in C++ (and C) Applications | 0.2.18 | 0.2.18 |
rintrojs Wrapper for the 'Intro.js' Library | 0.3.2 | 0.3.2 |
rio A Swiss-Army Knife for Data I/O | 0.5.29 | 0.5.29 |
Risk Computes 26 Financial Risk Measures for Any Continuous Distribution | 1.0 | 1.0 |
riskParityPortfolio Design of Risk Parity Portfolios | 0.2.2 | 0.2.2 |
RiskPortfolios Computation of Risk-Based Portfolios | 2.1.7 | 2.1.7 |
riskRegression Risk Regression Models and Prediction Scores for Survival Analysis with Competing Risks | 2022.03.22 | 2022.03.22 |
risksetROC Riskset ROC Curve Estimation from Censored Survival Data | 1.0.4.1 | 1.0.4.1 |
riskSimul Risk Quantification for Stock Portfolios under the T-Copula Model | 0.1.1 | 0.1.1 |
ritis Integrated Taxonomic Information System Client | 1.0.0 | 1.0.0 |
RItools Randomization Inference Tools | 0.1-18 | 0.1-18 |
riverdist River Network Distance Computation and Applications | 0.15.5 | 0.15.5 |
rivernet Read, Analyze and Plot River Networks | 1.2.1 | 1.2.1 |
rjags Bayesian Graphical Models using MCMC | 4-12 | 4-12 |
rJava Low-Level R to Java Interface | 1.0-6 | 1.0-6 |
RJDBC Provides Access to Databases Through the JDBC Interface | 0.2-10 | 0.2-10 |
RJDemetra Interface to 'JDemetra+' Seasonal Adjustment Software | 0.2.0 | 0.2.0 |
rje Miscellaneous Useful Functions for Statistics | 1.12.1 | 1.12.1 |
rjson JSON for R | 0.2.21 | 0.2.21 |
rjsonapi Consumer for APIs that Follow the JSON API Specification | 0.1.0 | 0.1.0 |
RJSONIO Serialize R Objects to JSON, JavaScript Object Notation | 1.3-1.8 | 1.3-1.8 |
rjstat Handle 'JSON-stat' Format in R | 0.4.2 | 0.4.2 |
rJython R interface to Python via Jython | 0.0-4 | 0.0-4 |
RKEA R/KEA Interface | 0.0-6 | 0.0-6 |
RKEAjars R/KEA Interface Jars | 5.0-4 | 5.0-4 |
rlang Functions for Base Types and Core R and 'Tidyverse' Features | 1.1.0 | 1.1.0 |
rle Common Functions for Run-Length Encoded Vectors | 0.9.2 | 0.9.2 |
rlecuyer R Interface to RNG with Multiple Streams | 0.3-7 | 0.3-7 |
rlemon R Access to LEMON Graph Algorithms | 0.2.0 | 0.2.0 |
Rlibeemd Ensemble Empirical Mode Decomposition (EEMD) and Its Complete Variant (CEEMDAN) | 1.4.2 | 1.4.2 |
Rlinsolve Iterative Solvers for (Sparse) Linear System of Equations | 0.3.2 | 0.3.2 |
rlist A Toolbox for Non-Tabular Data Manipulation | 0.4.6.2 | 0.4.6.2 |
RLRsim Exact (Restricted) Likelihood Ratio Tests for Mixed and Additive Models | 3.1-8 | 3.1-8 |
RLT Reinforcement Learning Trees | 3.2.5 | 3.2.5 |
rLTP R Interface to the 'LTP'-Cloud Service | 0.1.4 | 0.1.4 |
RLumShiny 'Shiny' Applications for the R Package 'Luminescence' | 0.2.3 | 0.2.3 |
RM2006 RiskMetrics 2006 Methodology | 0.1.1 | 0.1.1 |
rma.exact Exact Confidence Intervals for Random Effects Meta-Analyses | 0.1.0 | 0.1.0 |
rmaf Refined Moving Average Filter | 3.0.1 | 3.0.1 |
Rmagic MAGIC - Markov Affinity-Based Graph Imputation of Cells | 2.0.3 | 2.0.3 |
Rmalschains Continuous Optimization using Memetic Algorithms with Local Search Chains (MA-LS-Chains) in R | 0.2-9 | 0.2-9 |
rmapshaper Client for 'mapshaper' for 'Geospatial' Operations | 0.4.5 | 0.4.5 |
RMariaDB Database Interface and MariaDB Driver | 1.2.2 | 1.2.2 |
rmarkdown Dynamic Documents for R | 2.14 | 2.14 |
rmatio Read and Write 'Matlab' Files | 0.18.0 | 0.18.0 |
RMAWGEN Multi-Site Auto-Regressive Weather GENerator | 1.3.7 | 1.3.7 |
rmdformats HTML Output Formats and Templates for 'rmarkdown' Documents | 1.0.3 | 1.0.3 |
rmeta Meta-Analysis | 3.0 | 3.0 |
rmetasim An Individual-Based Population Genetic Simulation Environment | 3.1.14 | 3.1.14 |
rmgarch Multivariate GARCH Models | 1.3-9 | 1.3-9 |
rminer Data Mining Classification and Regression Methods | 1.4.6 | 1.4.6 |
rmio Provides 'mio' C++11 Header Files | 0.4.0 | 0.4.0 |
Rmisc Ryan Miscellaneous | 1.5.1 | 1.5.1 |
Rmixmod Classification with Mixture Modelling | 2.1.8 | 2.1.8 |
RMixtComp Mixture Models with Heterogeneous and (Partially) Missing Data | 4.1.3 | 4.1.3 |
RMixtCompIO Minimal Interface of the C++ 'MixtComp' Library for Mixture Models with Heterogeneous and (Partially) Missing Data | 4.0.9 | 4.0.9 |
RMixtCompUtilities Utility Functions for 'MixtComp' Outputs | 4.1.4 | 4.1.4 |
RMKdiscrete Sundry Discrete Probability Distributions | 0.2 | 0.2 |
Rmosek The R to MOSEK Optimization Interface | 1.3.5 | 1.3.5 |
Rmpfr R MPFR - Multiple Precision Floating-Point Reliable | 0.9-1 | 0.9-1 |
Rmpi Interface (Wrapper) to MPI (Message-Passing Interface) | 0.7-1 | 0.7-1 |
rms Regression Modeling Strategies | 6.5-0 | 6.5-0 |
rmsfact Amazing Random Facts About the World's Greatest Hacker | 0.0.3 | 0.0.3 |
RMTstat Distributions, Statistics and Tests Derived from Random Matrix Theory | 0.3.1 | 0.3.1 |
rmutil Utilities for Nonlinear Regression and Repeated Measurements Models | 1.1.10 | 1.1.10 |
RMySQL Database Interface and 'MySQL' Driver for R | 0.10.25 | 0.10.25 |
RNAseqNet Log-Linear Poisson Graphical Model with Hot-Deck Multiple Imputation | 0.1.4 | 0.1.4 |
rnaturalearth World Map Data from Natural Earth | 0.1.0 | 0.1.0 |
rnaturalearthdata World Vector Map Data from Natural Earth Used in 'rnaturalearth' | 0.1.0 | 0.1.0 |
RNCEP Obtain, Organize, and Visualize NCEP Weather Data | 1.0.10 | 1.0.10 |
rncl An Interface to the Nexus Class Library | 0.8.7 | 0.8.7 |
RND Risk Neutral Density Extraction Package | 1.2 | 1.2 |
rneos XML-RPC Interface to NEOS | 0.4-0 | 0.4-0 |
RNetCDF Interface to 'NetCDF' Datasets | 2.6-2 | 2.6-2 |
RNeXML Semantically Rich I/O for the 'NeXML' Format | 2.4.11 | 2.4.11 |
rngtools Utility Functions for Working with Random Number Generators | 1.5.2 | 1.5.2 |
rngWELL Toolbox for WELL Random Number Generators | 0.10-9 | 0.10-9 |
rngwell19937 Random number generator WELL19937a with 53 or 32 bit output | 0.6-0 | 0.6-0 |
RNifti Fast R and C++ Access to NIfTI Images | 1.4.5 | 1.4.5 |
RNiftyReg Image Registration Using the 'NiftyReg' Library | 2.7.1 | 2.7.1 |
rnoaa 'NOAA' Weather Data from R | 1.3.8 | 1.3.8 |
rnrfa UK National River Flow Archive Data from R | 2.0.4 | 2.0.4 |
roadoi Find Free Versions of Scholarly Publications via Unpaywall | 0.7.2 | 0.7.2 |
ROAuth R Interface For OAuth | 0.9.6 | 0.9.6 |
RobAStBase Robust Asymptotic Statistics | 1.2.3 | 1.2.3 |
robcor Robust Correlations | 0.1-6.1 | 0.1-6.1 |
robcp Robust Change-Point Tests | 0.3.3 | 0.3.3 |
robeth R Functions for Robust Statistics | 2.7-6 | 2.7-6 |
robets Forecasting Time Series with Robust Exponential Smoothing | 1.4 | 1.4 |
robfilter Robust Time Series Filters | 4.1.3 | 4.1.3 |
RobLox Optimally Robust Influence Curves and Estimators for Location and Scale | 1.2.0 | 1.2.0 |
RobLoxBioC Infinitesimally Robust Estimators for Preprocessing -Omics Data | 1.2.0 | 1.2.0 |
robmixglm Robust Generalized Linear Models (GLM) using Mixtures | 1.2-2 | 1.2-2 |
robotstxt A 'robots.txt' Parser and 'Webbot'/'Spider'/'Crawler' Permissions Checker | 0.7.13 | 0.7.13 |
RobPer Robust Periodogram and Periodicity Detection Methods | 1.2.3 | 1.2.3 |
RobRex Optimally Robust Influence Curves for Regression and Scale | 1.2.0 | 1.2.0 |
RobRSVD Robust Regularized Singular Value Decomposition | 1.0 | 1.0 |
robumeta Robust Variance Meta-Regression | 2.0 | 2.0 |
robust Port of the S+ "Robust Library" | 0.7-1 | 0.7-1 |
RobustAFT Truncated Maximum Likelihood Fit and Robust Accelerated Failure Time Regression for Gaussian and Log-Weibull Case | 1.4-5 | 1.4-5 |
robustarima Robust ARIMA Modeling | 0.2.6 | 0.2.6 |
robustbase Basic Robust Statistics | 0.95-0 | 0.95-0 |
robustDA Robust Mixture Discriminant Analysis | 1.2 | 1.2 |
robustgam Robust Estimation for Generalized Additive Models | 0.1.7 | 0.1.7 |
robustHD Robust Methods for High-Dimensional Data | 0.7.4 | 0.7.4 |
robustlmm Robust Linear Mixed Effects Models | 3.1-1 | 3.1-1 |
robustrank Robust Rank-Based Tests | 2019.9-10 | 2019.9-10 |
RobustRankAggreg Methods for Robust Rank Aggregation | 1.2.1 | 1.2.1 |
robustrao An Extended Rao-Stirling Diversity Index to Handle Missing Data | 1.0-5 | 1.0-5 |
robustreg Robust Regression Functions | 0.1-11 | 0.1-11 |
robustX 'eXtra' / 'eXperimental' Functionality for Robust Statistics | 1.2-6 | 1.2-6 |
rockchalk Regression Estimation and Presentation | 1.8.157 | 1.8.157 |
ROCR Visualizing the Performance of Scoring Classifiers | 1.0-11 | 1.0-11 |
RODBC ODBC Database Access | 1.3-20 | 1.3-20 |
rODE Ordinary Differential Equation (ODE) Solvers Written in R Using S4 Classes | 0.99.6 | 0.99.6 |
rodeo A Code Generator for ODE-Based Models | 0.7.7 | 0.7.7 |
ROI R Optimization Infrastructure | 1.0-0 | 1.0-0 |
ROI.plugin.clp 'Clp (Coin-or linear programming)' Plugin for the 'R' Optimization Interface | 0.4 | 0.4 |
ROI.plugin.glpk 'ROI' Plug-in 'GLPK' | 1.0-0 | 1.0-0 |
ROI.plugin.neos 'NEOS' Plug-in for the 'R' Optimization Interface | 1.0-0 | 1.0-0 |
ROI.plugin.qpoases 'qpOASES' Plugin for the 'R' Optimization Infrastructure | 1.0-2 | 1.0-2 |
roll Rolling and Expanding Statistics | 1.1.6 | 1.1.6 |
ROOPSD R Object Oriented Programming for Statistical Distribution | 0.3.8 | 0.3.8 |
RootsExtremaInflections Finds Roots, Extrema and Inflection Points of a Curve | 1.2.1 | 1.2.1 |
rootSolve Nonlinear Root Finding, Equilibrium and Steady-State Analysis of Ordinary Differential Equations | 1.8.2.3 | 1.8.2.3 |
ROpenFIGI R Interface to OpenFIGI | 0.2.8 | 0.2.8 |
ROpenWeatherMap R Interface to OpenWeatherMap API | 1.1 | 1.1 |
roperators Additional Operators to Help you Write Cleaner R Code | 1.2.0 | 1.2.0 |
ROptEst Optimally Robust Estimation | 1.3.1 | 1.3.1 |
ROptEstOld Optimally Robust Estimation - Old Version | 1.2.0 | 1.2.0 |
roptim General Purpose Optimization in R using C++ | 0.1.6 | 0.1.6 |
ROptRegTS Optimally Robust Estimation for Regression-Type Models | 1.2.0 | 1.2.0 |
ROptSpace Matrix Reconstruction from a Few Entries | 0.2.3 | 0.2.3 |
rorcid Interface to the 'Orcid.org' API | 0.7.0 | 0.7.0 |
rorutadis Robust Ordinal Regression UTADIS | 0.4.2 | 0.4.2 |
rosetteApi 'Rosette' API | 1.14.4 | 1.14.4 |
rosm Plot Raster Map Tiles from Open Street Map and Other Sources | 0.2.5 | 0.2.5 |
rospca Robust Sparse PCA using the ROSPCA Algorithm | 1.0.4 | 1.0.4 |
rotl Interface to the 'Open Tree of Life' API | 3.0.14 | 3.0.14 |
RoughSets Data Analysis Using Rough Set and Fuzzy Rough Set Theories | 1.3-7 | 1.3-7 |
routr A Simple Router for HTTP and WebSocket Requests | 0.4.1 | 0.4.1 |
roxygen2 In-Line Documentation for R | 7.2.2 | 7.2.2 |
rpact Confirmatory Adaptive Clinical Trial Design and Analysis | 3.2.3 | 3.2.3 |
rpanel Simple Interactive Controls for R using the 'tcltk' Package | 1.1-5.2 | 1.1-5.2 |
rpart Recursive Partitioning and Regression Trees | 4.1.19 | 4.1.19 |
rpart.plot Plot 'rpart' Models: An Enhanced Version of 'plot.rpart' | 3.1.1 | 3.1.1 |
rpatrec Recognising Visual Charting Patterns in Time Series Data | 1.0.1 | 1.0.1 |
rpca RobustPCA: Decompose a Matrix into Low-Rank and Sparse Components | 0.2.3 | 0.2.3 |
rpdo Pacific Decadal Oscillation Index Data | 0.3.1 | 0.3.1 |
rpf Response Probability Functions | 1.0.11 | 1.0.11 |
Rphylip An R interface for PHYLIP | 0.1-23 | 0.1-23 |
rpinterest Access Pinterest API | 0.3.1 | 0.3.1 |
rplos Interface to the Search API for 'PLoS' Journals | 1.0.0 | 1.0.0 |
RPMG Graphical User Interface (GUI) for Interactive R Analysis Sessions | 2.2-3 | 2.2-3 |
RPMM Recursively Partitioned Mixture Model | 1.25 | 1.25 |
rpms Recursive Partitioning for Modeling Survey Data | 0.5.1 | 0.5.1 |
rpostgis R Interface to a 'PostGIS' Database | 1.4.3 | 1.4.3 |
rpostgisLT Managing Animal Movement Data with 'PostGIS' and R | 0.6.0 | 0.6.0 |
RPostgres Rcpp Interface to PostgreSQL | 1.4.5 | 1.4.5 |
RPostgreSQL R Interface to the 'PostgreSQL' Database System | 0.7-5 | 0.7-5 |
rppo Access the Global Plant Phenology Data Portal | 1.0.1 | 1.0.1 |
RPresto DBI Connector to Presto | 1.4.4 | 1.4.4 |
rprintf Adaptive Builder for Formatted Strings | 0.2.1 | 0.2.1 |
rprojroot Finding Files in Project Subdirectories | 2.0.3 | 2.0.3 |
RProtoBuf R Interface to the 'Protocol Buffers' 'API' (Version 2 or 3) | 0.4.20 | 0.4.20 |
rpubchem An Interface to the PubChem Collection | 1.5.10 | 1.5.10 |
RPushbullet R Interface to the Pushbullet Messaging Service | 0.3.4 | 0.3.4 |
RPyGeo ArcGIS Geoprocessing via Python | 1.0.0 | 1.0.0 |
rqdatatable 'rquery' for 'data.table' | 1.3.1 | 1.3.1 |
RQuantLib R Interface to the 'QuantLib' Library | 0.4.16 | 0.4.16 |
rquery Relational Query Generator for Data Manipulation at Scale | 1.4.9 | 1.4.9 |
rrcov Scalable Robust Estimators with High Breakdown Point | 1.7-2 | 1.7-2 |
rrcov3way Robust Methods for Multiway Data Analysis, Applicable also for Compositional Data | 0.2-3 | 0.2-3 |
rrcovHD Robust Multivariate Methods for High Dimensional Data | 0.2-7 | 0.2-7 |
rrcovNA Scalable Robust Estimators with High Breakdown Point for Incomplete Data | 0.4-15 | 0.4-15 |
rredis "Redis" Key/Value Database Client | 1.7.0 | 1.7.0 |
rredlist 'IUCN' Red List Client | 0.7.1 | 0.7.1 |
rrefine r Client for OpenRefine API | 2.1.0 | 2.1.0 |
rromeo Access Publisher Copyright & Self-Archiving Policies via the 'SHERPA/RoMEO' API | 0.1.1 | 0.1.1 |
RRPP Linear Model Evaluation with Randomized Residuals in a Permutation Procedure | 1.2.3 | 1.2.3 |
RRreg Correlation and Regression Analyses for Randomized Response Data | 0.7.5 | 0.7.5 |
RRTCS Randomized Response Techniques for Complex Surveys | 0.0.4 | 0.0.4 |
rrum Bayesian Estimation of the Reduced Reparameterized Unified Model with Gibbs Sampling | 0.2.0 | 0.2.0 |
rsae Robust Small Area Estimation | 0.2 | 0.2 |
RSAlgaeR Builds Empirical Remote Sensing Models of Water Quality Variables and Analyzes Long-Term Trends | 1.0.0 | 1.0.0 |
rsample General Resampling Infrastructure | 1.1.1 | 1.1.1 |
Rsamtools | 2.12.0 | 2.12.0 |
rsatscan Tools, Classes, and Methods for Interfacing with SaTScan Stand-Alone Software | 0.3.9200 | 0.3.9200 |
RSauceLabs R Wrapper for 'SauceLabs' REST API | 0.1.6 | 0.1.6 |
RSclient Client for Rserve | 0.7-8 | 0.7-8 |
rsconnect Deployment Interface for R Markdown Documents and Shiny Applications | 0.8.25 | 0.8.25 |
rscopus Scopus Database 'API' Interface | 0.6.6 | 0.6.6 |
rsdmx Tools for Reading SDMX Data and Metadata | 0.6 | 0.6 |
RSEIS Seismic Time Series Analysis Tools | 4.1-4 | 4.1-4 |
RSelenium R Bindings for 'Selenium WebDriver' | 1.7.9 | 1.7.9 |
rsem Robust Structural Equation Modeling with Missing Data and Auxiliary Variables | 0.5.0 | 0.5.0 |
RSGHB Functions for Hierarchical Bayesian Estimation: A Flexible Approach | 1.2.2 | 1.2.2 |
RSiena Siena - Simulation Investigation for Empirical Network Analysis | 1.3.0.1 | 1.3.0.1 |
RSiteCatalyst R Client for Adobe Analytics API V1.4 | 1.4.16 | 1.4.16 |
RSKC Robust Sparse K-Means | 2.4.2 | 2.4.2 |
rslurm Submit R Calculations to a 'Slurm' Cluster | 0.6.2 | 0.6.2 |
rsm Response-Surface Analysis | 2.10.3 | 2.10.3 |
RSmartlyIO Loading Facebook and Instagram Advertising Data from 'Smartly.io' | 0.1.3 | 0.1.3 |
rsMove Guidelines for the use of Remote Sensing in Movement Ecology | 0.2.8 | 0.2.8 |
RSNNS Neural Networks using the Stuttgart Neural Network Simulator (SNNS) | 0.4-15 | 0.4-15 |
rsoi Import Various Northern and Southern Hemisphere Climate Indices | 0.5.5 | 0.5.5 |
Rsolnp General Non-Linear Optimization | 1.16 | 1.16 |
rspa Adapt Numerical Records to Fit (in)Equality Restrictions | 0.2.8 | 0.2.8 |
rsparse Statistical Learning on Sparse Matrices | 0.5.1 | 0.5.1 |
RSpectra Solvers for Large-Scale Eigenvalue and SVD Problems | 0.16-1 | 0.16-1 |
RSQLite SQLite Interface for R | 2.3.0 | 2.3.0 |
Rssa A Collection of Methods for Singular Spectrum Analysis | 1.0.5 | 1.0.5 |
rstan R Interface to Stan | 2.21.7 | 2.21.7 |
rstantools Tools for Developing R Packages Interfacing with 'Stan' | 2.2.0 | 2.2.0 |
rstatix Pipe-Friendly Framework for Basic Statistical Tests | 0.7.2 | 0.7.2 |
rstiefel Random Orthonormal Matrix Generation and Optimization on the Stiefel Manifold | 1.0.1 | 1.0.1 |
rstpm2 Smooth Survival Models, Including Generalized Survival Models | 1.6.2 | 1.6.2 |
rstream Streams of Random Numbers | 1.3.7 | 1.3.7 |
RStripe A Convenience Interface for the Stripe Payment API | 0.1 | 0.1 |
rstudioapi Safely Access the RStudio API | 0.14 | 0.14 |
RSuite Supports Developing, Building and Deploying R Solution | 0.37-253 | 0.37-253 |
rsurface Design of Rotatable Central Composite Experiments and Response Surface Analysis | 1.1.0 | 1.1.0 |
RSurvey Geographic Information System Application | 0.9.3 | 0.9.3 |
rsvd Randomized Singular Value Decomposition | 1.0.5 | 1.0.5 |
rsvg Render SVG Images into PDF, PNG, (Encapsulated) PostScript, or Bitmap Arrays | 2.3.1 | 2.3.1 |
RSvgDevice An R SVG graphics device. | 0.6.4.4 | 0.6.4.4 |
RSVGTipsDevice An R SVG Graphics Device with Dynamic Tips and Hyperlinks | 1.0-7 | 1.0-7 |
Rsymphony SYMPHONY in R | 0.1-33 | 0.1-33 |
rSymPy R Interface to SymPy Computer Algebra System | 0.2-1.2 | 0.2-1.2 |
Rtauchen Discretization of AR(1) Processes | 1.0 | 1.0 |
RTDE Robust Tail Dependence Estimation | 0.2-1 | 0.2-1 |
rtdists Response Time Distributions | 0.11-5 | 0.11-5 |
rTensor Tools for Tensor Analysis and Decomposition | 1.4.8 | 1.4.8 |
rtf Rich Text Format (RTF) Output | 0.4-14.1 | 0.4-14.1 |
rticles Article Formats for R Markdown | 0.23 | 0.23 |
rtkore 'STK++' Core Library Integration to 'R' using 'Rcpp' | 1.6.7 | 1.6.7 |
Rtnmin Truncated Newton Function Minimization with Bounds Constraints | 2016-7.7 | 2016-7.7 |
rtop Interpolation of Data with Variable Spatial Support | 0.6-2 | 0.6-2 |
rtracklayer | 1.56.0 | 1.56.0 |
RTransferEntropy Measuring Information Flow Between Time Series with Shannon and Renyi Transfer Entropy | 0.2.21 | 0.2.21 |
rtrek Datasets and Functions Relating to Star Trek | 0.3.3 | 0.3.3 |
rts Raster Time Series Analysis | 1.1-8 | 1.1-8 |
Rtsne T-Distributed Stochastic Neighbor Embedding using a Barnes-Hut Implementation | 0.16 | 0.16 |
Rttf2pt1 'ttf2pt1' Program | 1.3.12 | 1.3.12 |
rtweet Collecting Twitter Data | 1.1.0 | 1.1.0 |
rucrdtw R Bindings for the UCR Suite | 0.1.4 | 0.1.4 |
rugarch Univariate GARCH Models | 1.4-9 | 1.4-9 |
ruimtehol Learn Text 'Embeddings' with 'Starspace' | 0.3.1 | 0.3.1 |
rUnemploymentData Data and Functions for USA State and County Unemployment Data | 1.1.0 | 1.1.0 |
RUnit R Unit Test Framework | 0.4.32 | 0.4.32 |
runjags Interface Utilities, Model Templates, Parallel Computing Methods and Additional Distributions for MCMC Models in JAGS | 2.2.1-7 | 2.2.1-7 |
runner Running Operations for Vectors | 0.4.3 | 0.4.3 |
runstats Fast Computation of Running Statistics for Time Series | 1.1.0 | 1.1.0 |
Runuran R Interface to the 'UNU.RAN' Random Variate Generators | 0.36 | 0.36 |
rust Ratio-of-Uniforms Simulation with Transformation | 1.4.0 | 1.4.0 |
Rvcg Manipulations of Triangular Meshes Based on the 'VCGLIB' API | 0.22.1 | 0.22.1 |
rversions Query 'R' Versions, Including 'r-release' and 'r-oldrel' | 2.1.2 | 2.1.2 |
rvertnet Search 'Vertnet', a 'Database' of Vertebrate Specimen Records | 0.8.2 | 0.8.2 |
rvest Easily Harvest (Scrape) Web Pages | 1.0.3 | 1.0.3 |
rvg R Graphics Devices for 'Office' Vector Graphics Output | 0.2.5 | 0.2.5 |
RViennaCL 'ViennaCL' C++ Header Files | 1.7.1.8 | 1.7.1.8 |
Rvmmin Variable Metric Nonlinear Function Minimization | 2018-4.17.1 | 2018-4.17.1 |
Rwave Time-Frequency Analysis of 1-D Signals | 2.6-5 | 2.6-5 |
RWeka R/Weka Interface | 0.4-46 | 0.4-46 |
RWekajars R/Weka Interface Jars | 3.9.3-2 | 3.9.3-2 |
RWiener Wiener Process Distribution Functions | 1.3-3 | 1.3-3 |
rworldmap Mapping Global Data | 1.3-6 | 1.3-6 |
rworldxtra Country boundaries at high resolution. | 1.01 | 1.01 |
rwt 'Rice Wavelet Toolbox' Wrapper | 1.0.2 | 1.0.2 |
rwunderground R Interface to Weather Underground API | 0.1.8 | 0.1.8 |
RxCEcolInf 'R x C Ecological Inference With Optional Incorporation of Survey Information' | 0.1-5 | 0.1-5 |
RxODE Facilities for Simulating from ODE-Based Models | 1.1.5 | 1.1.5 |
RXshrink Maximum Likelihood Shrinkage using Generalized Ridge or Least Angle Regression | 2.2 | 2.2 |
Ryacas R Interface to the 'Yacas' Computer Algebra System | 1.1.5 | 1.1.5 |
RYandexTranslate R Interface to Yandex Translate API | 1.0 | 1.0 |
RZabbix R Module for Working with the 'Zabbix API' | 0.1.0 | 0.1.0 |
s2 Spherical Geometry Operators Using the S2 Geometry Library | 1.0.7 | 1.0.7 |
s20x Functions for University of Auckland Course STATS 201/208 Data Analysis | 3.1-36 | 3.1-36 |
S2sls Spatial Two Stage Least Squares Estimation | 0.1 | 0.1 |
S4Vectors | 0.34.0 | 0.34.0 |
saccades Detection of Fixations in Eye-Tracking Data | 0.1-1 | 0.1-1 |
SACOBRA Self-Adjusting COBRA | 1.2 | 1.2 |
sadists Some Additional Distributions | 0.2.4 | 0.2.4 |
sae Small Area Estimation | 1.3 | 1.3 |
saemix Stochastic Approximation Expectation Maximization (SAEM) Algorithm | 3.0 | 3.0 |
saeRobust Robust Small Area Estimation | 0.4.0 | 0.4.0 |
saeSim Simulation Tools for Small Area Estimation | 0.11.0 | 0.11.0 |
SamplerCompare A Framework for Comparing the Performance of MCMC Samplers | 1.3.2 | 1.3.2 |
sampleSelection Sample Selection Models | 1.2-12 | 1.2-12 |
samplesize Sample Size Calculation for Various t-Tests and Wilcoxon-Test | 0.2-4 | 0.2-4 |
SampleSizeMeans Sample Size Calculations for Normal Means | 1.1 | 1.1 |
SampleSizeProportions Calculating Sample Size Requirements when Estimating the Difference Between Two Binomial Proportions | 1.0 | 1.0 |
sampling Survey Sampling | 2.9 | 2.9 |
SamplingBigData Sampling Methods for Big Data | 1.0.0 | 1.0.0 |
samplingbook Survey Sampling Procedures | 1.2.4 | 1.2.4 |
SamplingStrata Optimal Stratification of Sampling Frames for Multipurpose Sampling Surveys | 1.5-4 | 1.5-4 |
samplingVarEst Sampling Variance Estimation | 1.5 | 1.5 |
SAMURAI Sensitivity Analysis of a Meta-analysis with Unpublished but Registered Analytical Investigations | 1.2.1 | 1.2.1 |
sandwich Robust Covariance Matrix Estimators | 3.0-2 | 3.0-2 |
santaR Short Asynchronous Time-Series Analysis | 1.2.0 | 1.2.0 |
sapa Spectral Analysis for Physical Applications | 2.0-2 | 2.0-2 |
sarima Simulation and Prediction with Seasonal ARIMA Models | 0.9.1 | 0.9.1 |
SAScii Import ASCII Files Directly into R using Only a 'SAS' Input Script | 1.0.1 | 1.0.1 |
sass Syntactically Awesome Style Sheets ('Sass') | 0.4.5 | 0.4.5 |
satellite Handling and Manipulating Remote Sensing Data | 1.0.4 | 1.0.4 |
saws Small-Sample Adjustments for Wald Tests Using Sandwich Estimators | 0.9-7.0 | 0.9-7.0 |
sazedR Parameter-Free Domain-Agnostic Season Length Detection in Time Series | 2.0.2 | 2.0.2 |
sbgcop Semiparametric Bayesian Gaussian Copula Estimation and Imputation | 0.980 | 0.980 |
sbm Stochastic Blockmodels | 0.4.5 | 0.4.5 |
scagnostics Compute scagnostics - scatterplot diagnostics | 0.2-6 | 0.2-6 |
ScaledMatrix | 1.4.1 | 1.4.1 |
scales Scale Functions for Visualization | 1.2.1 | 1.2.1 |
scalreg Scaled Sparse Linear Regression | 1.0.1 | 1.0.1 |
scam Shape Constrained Additive Models | 1.2-13 | 1.2-13 |
scaRabee Optimization Toolkit for Pharmacokinetic-Pharmacodynamic Models | 1.1-4 | 1.1-4 |
scatterD3 D3 JavaScript Scatterplot from R | 1.0.1 | 1.0.1 |
scattermore Scatterplots with More Points | 0.8 | 0.8 |
scatterplot3d 3D Scatter Plot | 0.3-43 | 0.3-43 |
SCBmeanfd Simultaneous Confidence Bands for the Mean of Functional Data | 1.2.2 | 1.2.2 |
SCEPtER Stellar CharactEristics Pisa Estimation gRid | 0.2-4 | 0.2-4 |
SCEPtERbinary Stellar CharactEristics Pisa Estimation gRid for Binary Systems | 0.1-1 | 0.1-1 |
scholar Analyse Citation Data from Google Scholar | 0.2.4 | 0.2.4 |
schumaker Schumaker Shape-Preserving Spline | 1.2.1 | 1.2.1 |
SCI Standardized Climate Indices Such as SPI, SRI or SPEI | 1.0-2 | 1.0-2 |
SCMA Single-Case Meta-Analysis | 1.3.1 | 1.3.1 |
SCOR Spherically Constrained Optimization Routine | 1.1.1 | 1.1.1 |
scorecardModelUtils Credit Scorecard Modelling Utils | 0.0.1.0 | 0.0.1.0 |
scoringRules Scoring Rules for Parametric and Simulated Distribution Forecasts | 1.0.2 | 1.0.2 |
scran | 1.24.1 | 1.24.1 |
scrapeR Tools for Scraping Data from HTML and XML Documents | 0.1.6 | 0.1.6 |
SCRT Single-Case Randomization Tests | 1.3.1 | 1.3.1 |
scs Splitting Conic Solver | 3.0-1 | 3.0-1 |
sctransform Variance Stabilizing Transformations for Single Cell UMI Data | 0.3.3 | 0.3.3 |
scuttle | 1.6.3 | 1.6.3 |
sda Shrinkage Discriminant Analysis and CAT Score Variable Selection | 1.3.8 | 1.3.8 |
SDaA Sampling: Design and Analysis | 0.1-5 | 0.1-5 |
sdcHierarchies Create and (Interactively) Modify Nested Hierarchies | 0.19.3 | 0.19.3 |
sdcSpatial Statistical Disclosure Control for Spatial Data | 0.5.2 | 0.5.2 |
sdcTable Methods for Statistical Disclosure Control in Tabular Data | 0.32.4 | 0.32.4 |
SDD Serial Dependence Diagrams | 1.2 | 1.2 |
sde Simulation and Inference for Stochastic Differential Equations | 2.0.18 | 2.0.18 |
SDLfilter Filtering and Assessing the Sample Size of Tracking Data | 2.3.1 | 2.3.1 |
sdpt3r Semi-Definite Quadratic Linear Programming Solver | 0.3 | 0.3 |
seacarb Seawater Carbonate Chemistry | 3.3.1 | 3.3.1 |
searchConsoleR Google Search Console R Client | 0.4.0 | 0.4.0 |
searcher Query Search Interfaces | 0.0.6 | 0.0.6 |
seas Seasonal Analysis and Graphics, Especially for Climatology | 0.6-0 | 0.6-0 |
season Seasonal Analysis of Health Data | 0.3.15 | 0.3.15 |
seasonal R Interface to X-13-ARIMA-SEATS | 1.9.0 | 1.9.0 |
seasonalview Graphical User Interface for Seasonal Adjustment | 0.3 | 0.3 |
seastests Seasonality Tests | 0.15.4 | 0.15.4 |
secr Spatially Explicit Capture-Recapture | 4.5.10 | 4.5.10 |
securitytxt Identify and Parse Web Security Policies Files | 0.1.1 | 0.1.1 |
seewave Sound Analysis and Synthesis | 2.2.0 | 2.2.0 |
seg Measuring Spatial Segregation | 0.5-7 | 0.5-7 |
segclust2d Bivariate Segmentation/Clustering Methods and Tools | 0.3.0 | 0.3.0 |
segmented Regression Models with Break-Points / Change-Points (with Possibly Random Effects) Estimation | 1.6-1 | 1.6-1 |
SEL Semiparametric Elicitation | 1.0-3 | 1.0-3 |
selectMeta Estimation of Weight Functions in Meta Analysis | 1.0.8 | 1.0.8 |
selectr Translate CSS Selectors to XPath Expressions | 0.4-2 | 0.4-2 |
SeleMix Selective Editing via Mixture Models | 1.0.2 | 1.0.2 |
seleniumPipes R Client Implementing the W3C WebDriver Specification | 0.3.7 | 0.3.7 |
sem Structural Equation Models | 3.1-14 | 3.1-14 |
semdiag Structural equation modeling diagnostics | 0.1.2 | 0.1.2 |
semds Structural Equation Multidimensional Scaling | 0.9-6 | 0.9-6 |
SemiCompRisks Hierarchical Models for Parametric and Semi-Parametric Analyses of Semi-Competing Risks Data | 3.4 | 3.4 |
SemiMarkov Multi-States Semi-Markov Models | 1.4.6 | 1.4.6 |
seminr Building and Estimating Structural Equation Models | 2.3.0 | 2.3.0 |
SemiPar Semiparametic Regression | 1.0-4.2 | 1.0-4.2 |
SEMModComp Model Comparisons for SEM | 1.0 | 1.0 |
SemNeT Methods and Measures for Semantic Network Analysis | 1.4.3 | 1.4.3 |
SemNetCleaner An Automated Cleaning Tool for Semantic and Linguistic Data | 1.3.4 | 1.3.4 |
SemNetDictionaries Dictionaries for the 'SemNetCleaner' Package | 0.2.0 | 0.2.0 |
semPlot Path Diagrams and Visual Analysis of Various SEM Packages' Output | 1.1.5 | 1.1.5 |
semPLS Structural Equation Modeling Using Partial Least Squares | 1.0-10 | 1.0-10 |
semsfa Semiparametric Estimation of Stochastic Frontier Models | 1.1 | 1.1 |
semTools Useful Tools for Structural Equation Modeling | 0.5-4 | 0.5-4 |
semtree Recursive Partitioning for Structural Equation Models | 0.9.18 | 0.9.18 |
semver 'Semantic Versioning V2.0.0' Parser | 0.2.0 | 0.2.0 |
sendmailR Send Email Using R | 1.4-0 | 1.4-0 |
sensitivity Global Sensitivity Analysis of Model Outputs | 1.28.0 | 1.28.0 |
SensoMineR Sensory Data Analysis | 1.26 | 1.26 |
SentimentAnalysis Dictionary-Based Sentiment Analysis | 1.3-4 | 1.3-4 |
seqinr Biological Sequences Retrieval and Analysis | 4.2-23 | 4.2-23 |
seqMeta Meta-Analysis of Region-Based Tests of Rare DNA Variants | 1.6.7 | 1.6.7 |
seriation Infrastructure for Ordering Objects Using Seriation | 1.3.5 | 1.3.5 |
seroincidence Estimating Infection Rates from Serological Data | 2.0.0 | 2.0.0 |
servr A Simple HTTP Server to Serve Static Files or Dynamic Documents | 0.25 | 0.25 |
sessioninfo R Session Information | 1.2.2 | 1.2.2 |
set6 R6 Mathematical Sets Interface | 0.2.4 | 0.2.4 |
setRNG Set (Normal) Random Number Generator and Seed | 2022.4-1 | 2022.4-1 |
sets Sets, Generalized Sets, Customizable Sets and Intervals | 1.0-23 | 1.0-23 |
settings Software Option Settings Manager for R | 0.2.7 | 0.2.7 |
Seurat Tools for Single Cell Genomics | 4.1.1 | 4.1.1 |
SeuratObject Data Structures for Single Cell Data | 4.1.0 | 4.1.0 |
sf Simple Features for R | 0.9-8 | 0.9-8 |
sfa Stochastic Frontier Analysis | 1.0-1 | 1.0-1 |
sfheaders Converts Between R Objects and Simple Feature Objects | 0.4.2 | 0.4.2 |
sfsmisc Utilities from 'Seminar fuer Statistik' ETH Zurich | 1.1-14 | 1.1-14 |
sftime Classes and Methods for Simple Feature Objects that Have a Time Column | 0.2-0 | 0.2-0 |
sgd Stochastic Gradient Descent for Scalable Estimation | 1.1.1 | 1.1.1 |
sgeostat An Object-Oriented Framework for Geostatistical Modeling in S+ | 1.0-27 | 1.0-27 |
sgmodel Solves a Generic Stochastic Growth Model with a Representative Agent | 0.1.1 | 0.1.1 |
sgt Skewed Generalized T Distribution Tree | 2.0 | 2.0 |
shades Simple Colour Manipulation | 1.4.0 | 1.4.0 |
shape Functions for Plotting Graphical Shapes, Colors | 1.4.6 | 1.4.6 |
shapefiles Read and Write ESRI Shapefiles | 0.7.2 | 0.7.2 |
shapes Statistical Shape Analysis | 1.2.7 | 1.2.7 |
SharpeR Statistical Significance of the Sharpe Ratio | 1.3.0 | 1.3.0 |
sharpeRratio Moment-Free Estimation of Sharpe Ratios | 1.4.2 | 1.4.2 |
shiny Web Application Framework for R | 1.7.3 | 1.7.3 |
shinyAce Ace Editor Bindings for Shiny | 0.4.2 | 0.4.2 |
shinyBS Twitter Bootstrap Components for Shiny | 0.61.1 | 0.61.1 |
shinycssloaders Add Loading Animations to a 'shiny' Output While It's Recalculating | 1.0.0 | 1.0.0 |
shinydashboard Create Dashboards with 'Shiny' | 0.7.2 | 0.7.2 |
shinydashboardPlus Add More 'AdminLTE2' Components to 'shinydashboard' | 2.0.3 | 2.0.3 |
shinyFiles A Server-Side File System Viewer for Shiny | 0.9.3 | 0.9.3 |
ShinyItemAnalysis Test and Item Analysis via Shiny | 1.4.2 | 1.4.2 |
shinyjqui 'jQuery UI' Interactions and Effects for Shiny | 0.4.1 | 0.4.1 |
shinyjs Easily Improve the User Experience of Your Shiny Apps in Seconds | 2.1.0 | 2.1.0 |
shinystan Interactive Visual and Numerical Diagnostics and Posterior Analysis for Bayesian Models | 2.6.0 | 2.6.0 |
shinythemes Themes for Shiny | 1.2.0 | 1.2.0 |
shinyTree jsTree Bindings for Shiny | 0.2.7 | 0.2.7 |
shinyWidgets Custom Inputs Widgets for Shiny | 0.7.6 | 0.7.6 |
showimage Show an Image on an 'R' Graphics Device | 1.0.0 | 1.0.0 |
showtext Using Fonts More Easily in R Graphs | 0.9-5 | 0.9-5 |
showtextdb Font Files for the 'showtext' Package | 3.0 | 3.0 |
shp2graph Convert a SpatialLinesDataFrame Object to an 'igraph'-Class Object | 0-5 | 0-5 |
shutterstock Access 'Shutterstock' REST API | 0.1.0 | 0.1.0 |
sievePH Sieve Analysis Methods for Proportional Hazards Models | 1.0.4 | 1.0.4 |
sigclust Statistical Significance of Clustering | 1.1.0.1 | 1.1.0.1 |
sigmaNet Render Graphs Using 'Sigma.js' | 1.1.0 | 1.1.0 |
sigmoid Sigmoid Functions for Machine Learning | 1.4.0 | 1.4.0 |
signal Signal Processing | 0.7-7 | 0.7-7 |
SigTree Identify and Visualize Significantly Responsive Branches in a Phylogenetic Tree | 1.10.6 | 1.10.6 |
Sim.DiffProc Simulation of Diffusion Processes | 4.8 | 4.8 |
simba A Collection of functions for similarity analysis of vegetation data | 0.3-5 | 0.3-5 |
simcdm Simulate Cognitive Diagnostic Model ('CDM') Data | 0.1.1 | 0.1.1 |
simecol Simulation of Ecological (and Other) Dynamic Systems | 0.8-14 | 0.8-14 |
simex SIMEX- And MCSIMEX-Algorithm for Measurement Error Models | 1.8 | 1.8 |
simexaft simexaft | 1.0.7.1 | 1.0.7.1 |
simFrame Simulation Framework | 0.5.4 | 0.5.4 |
SimHaz Simulated Survival and Hazard Analysis for Time-Dependent Exposure | 0.1 | 0.1 |
SimilarityMeasures Trajectory Similarity Measures | 1.4 | 1.4 |
simMSM Simulation of Event Histories for Multi-State Models | 1.1.42 | 1.1.42 |
simPH Simulate and Plot Estimates from Cox Proportional Hazards Models | 1.3.13 | 1.3.13 |
simpleboot Simple Bootstrap Routines | 1.1-7 | 1.1-7 |
SimpleTable Bayesian Inference and Sensitivity Analysis for Causal Effects from 2 x 2 and 2 x 2 x K Tables in the Presence of Unmeasured Confounding | 0.1-2 | 0.1-2 |
SimplicialCubature Integration of Functions Over Simplices | 1.3 | 1.3 |
simPop Simulation of Complex Synthetic Data Information | 2.1.2 | 2.1.2 |
simputation Simple Imputation | 0.2.8 | 0.2.8 |
simrel Simulation of Multivariate Linear Model Data | 2.1.0 | 2.1.0 |
SiMRiv Simulating Multistate Movements in River/Heterogeneous Landscapes | 1.0.5 | 1.0.5 |
SimSCRPiecewise 'Simulates Univariate and Semi-Competing Risks Data Given Covariates and Piecewise Exponential Baseline Hazards' | 0.1.1 | 0.1.1 |
simsem SIMulated Structural Equation Modeling | 0.5-16 | 0.5-16 |
simsurv Simulate Survival Data | 1.0.0 | 1.0.0 |
SIN A SINful Approach to Selection of Gaussian Graphical Markov Models | 0.6 | 0.6 |
SingleCaseES A Calculator for Single-Case Effect Sizes | 0.7.1 | 0.7.1 |
SingleCellExperiment | 1.18.1 | 1.18.1 |
siplab Spatial Individual-Plant Modelling | 1.6 | 1.6 |
sirad Functions for Calculating Daily Solar Radiation and Evapotranspiration | 2.3-3 | 2.3-3 |
sirt Supplementary Item Response Theory Models | 3.12-66 | 3.12-66 |
SIS Sure Independence Screening | 0.8-8 | 0.8-8 |
sitmo Parallel Pseudo Random Number Generator (PPRNG) 'sitmo' Header Files | 2.0.2 | 2.0.2 |
sjlabelled Labelled Data Utility Functions | 1.2.0 | 1.2.0 |
sjmisc Data and Variable Transformation Functions | 2.8.9 | 2.8.9 |
sjPlot Data Visualization for Statistics in Social Science | 2.8.10 | 2.8.10 |
sjstats Collection of Convenient Functions for Common Statistical Computations | 0.18.1 | 0.18.1 |
SKAT SNP-Set (Sequence) Kernel Association Test | 2.2.5 | 2.2.5 |
skedastic Handling Heteroskedasticity in the Linear Regression Model | 1.0.4 | 1.0.4 |
skellam Densities and Sampling for the Skellam Distribution | 0.2.0 | 0.2.0 |
SkewHyperbolic The Skew Hyperbolic Student t-Distribution | 0.4-0 | 0.4-0 |
skewt The Skewed Student-t Distribution | 1.0 | 1.0 |
skmeans Spherical k-Means Clustering | 0.2-15 | 0.2-15 |
skpr Design of Experiments Suite: Generate and Evaluate Optimal Designs | 1.1.4 | 1.1.4 |
skynet Generates Networks from BTS Data | 1.4.0 | 1.4.0 |
slackr Send Messages, Images, R Objects and Files to 'Slack' Channels/Users | 3.3.1 | 3.3.1 |
slam Sparse Lightweight Arrays and Matrices | 0.1-50 | 0.1-50 |
sld Estimation and Use of the Quantile-Based Skew Logistic Distribution | 1.0.1 | 1.0.1 |
sleekts 4253H, Twice Smoothing | 1.0.2 | 1.0.2 |
Sleuth2 Data Sets from Ramsey and Schafer's "Statistical Sleuth (2nd Ed)" | 2.0-5 | 2.0-5 |
Sleuth3 Data Sets from Ramsey and Schafer's "Statistical Sleuth (3rd Ed)" | 1.0-3 | 1.0-3 |
slider Sliding Window Functions | 0.3.0 | 0.3.0 |
slippymath Slippy Map Tile Tools | 0.3.1 | 0.3.1 |
sm Smoothing Methods for Nonparametric Regression and Density Estimation | 2.2-5.7.1 | 2.2-5.7.1 |
smacof Multidimensional Scaling | 2.1-5 | 2.1-5 |
smacpod Statistical Methods for the Analysis of Case-Control Point Data | 2.5 | 2.5 |
SmallCountRounding Small Count Rounding of Tabular Data | 1.0.3 | 1.0.3 |
smam Statistical Modeling of Animal Movements | 0.6.0 | 0.6.0 |
smapr Acquisition and Processing of NASA Soil Moisture Active-Passive (SMAP) Data | 0.2.1 | 0.2.1 |
smatr (Standardised) Major Axis Estimation and Testing Routines | 3.4-8 | 3.4-8 |
smcfcs Multiple Imputation of Covariates by Substantive Model Compatible Fully Conditional Specification | 1.7.1 | 1.7.1 |
smcure Fit Semiparametric Mixture Cure Models | 2.1 | 2.1 |
smds Symbolic Multidimensional Scaling | 1.0 | 1.0 |
smerc Statistical Methods for Regional Counts | 1.6 | 1.6 |
SmithWilsonYieldCurve Smith-Wilson Yield Curve Construction | 1.0.1 | 1.0.1 |
smoof Single and Multi-Objective Optimization Test Functions | 1.6.0.3 | 1.6.0.3 |
smooth Forecasting Using State Space Models | 3.2.0 | 3.2.0 |
SmoothHazard Estimation of Smooth Hazard Models for Interval-Censored Data with Applications to Survival and Illness-Death Models | 2022.08.23 | 2022.08.23 |
smoothHR Smooth Hazard Ratio Curves Taking a Reference Value | 1.0.4 | 1.0.4 |
smoothmest Smoothed M-Estimators for 1-Dimensional Location | 0.1-3 | 0.1-3 |
smoots Nonparametric Estimation of the Trend and Its Derivatives in TS | 1.1.3 | 1.1.3 |
smovie Some Movies to Illustrate Concepts in Statistics | 1.1.4 | 1.1.4 |
SMPracticals Practicals for Use with Davison (2003) Statistical Models | 1.4-3 | 1.4-3 |
SMR Externally Studentized Midrange Distribution | 2.0.2 | 2.0.2 |
sms Spatial Microsimulation | 2.3.1 | 2.3.1 |
SMVar Structural Model for Variances | 1.3.4 | 1.3.4 |
sn The Skew-Normal and Related Distributions Such as the Skew-t and the SUN | 2.0.2 | 2.0.2 |
sna Tools for Social Network Analysis | 2.7-1 | 2.7-1 |
snakecase Convert Strings into any Case | 0.11.0 | 0.11.0 |
snapshot Gadget N-body cosmological simulation code snapshot I/O utilities | 0.1.2 | 0.1.2 |
snipEM Snipping Methods for Robust Estimation and Clustering | 1.0.1 | 1.0.1 |
snow Simple Network of Workstations | 0.4-4 | 0.4-4 |
SnowballC Snowball Stemmers Based on the C 'libstemmer' UTF-8 Library | 0.7.0 | 0.7.0 |
snowfall Easier Cluster Computing (Based on 'snow') | 1.84-6.2 | 1.84-6.2 |
snowFT Fault Tolerant Simple Network of Workstations | 1.6-0 | 1.6-0 |
snp.plotter snp.plotter | 0.5.1 | 0.5.1 |
SNPassoc SNPs-Based Whole Genome Association Studies | 2.0-11 | 2.0-11 |
SNPmaxsel Maximally selected statistics for SNP data | 1.0-3 | 1.0-3 |
snpStats | 1.44.0 | 1.44.0 |
soc.ca Specific Correspondence Analysis for the Social Sciences | 0.8.0 | 0.8.0 |
sodium A Modern and Easy-to-Use Crypto Library | 1.2.1 | 1.2.1 |
softImpute Matrix Completion via Iterative Soft-Thresholded SVD | 1.4-1 | 1.4-1 |
soiltexture Functions for Soil Texture Plot, Classification and Transformation | 1.5.1 | 1.5.1 |
soilwater Implementation of Parametric Formulas for Soil Water Retention or Conductivity Curve | 1.0.5 | 1.0.5 |
solaR Radiation and Photovoltaic Systems | 0.46 | 0.46 |
solartime Utilities Dealing with Solar Time Such as Sun Position and Time of Sunrise | 0.0.2 | 0.0.2 |
solrium General Purpose R Interface to 'Solr' | 1.2.0 | 1.2.0 |
SolveSAPHE Solver Suite for Alkalinity-PH Equations | 2.1.0 | 2.1.0 |
som Self-Organizing Map | 0.3-5.1 | 0.3-5.1 |
soma General-Purpose Optimisation with the Self-Organising Migrating Algorithm | 1.2.0 | 1.2.0 |
SortableHTMLTables Turns a data frame into an HTML file containing a sortable table. | 0.1-3 | 0.1-3 |
sorvi Functions for Finnish Open Data | 0.8.20 | 0.8.20 |
soundgen Sound Synthesis and Acoustic Analysis | 2.5.1 | 2.5.1 |
sourcetools Tools for Reading, Tokenizing and Parsing R Code | 0.1.7-1 | 0.1.7-1 |
sp Classes and Methods for Spatial Data | 1.6-0 | 1.6-0 |
spacefillr Space-Filling Random and Quasi-Random Sequences | 0.3.2 | 0.3.2 |
spacetime Classes and Methods for Spatio-Temporal Data | 1.2-8 | 1.2-8 |
SPADAR Spherical Projections of Astronomical Data | 1.0 | 1.0 |
spam SPArse Matrix | 2.9-1 | 2.9-1 |
spaMM Mixed-Effect Models, with or without Spatial Random Effects | 4.2.1 | 4.2.1 |
spanel Spatial Panel Data Models | 0.1 | 0.1 |
sparkbq Google 'BigQuery' Support for 'sparklyr' | 0.1.1 | 0.1.1 |
sparkline 'jQuery' Sparkline 'htmlwidget' | 2.0 | 2.0 |
sparklyr R Interface to Apache Spark | 1.8.0 | 1.8.0 |
sparktex Generate LaTeX sparklines in R | 0.1 | 0.1 |
sparr Spatial and Spatiotemporal Relative Risk | 2.3-10 | 2.3-10 |
sparsebn Learning Sparse Bayesian Networks from High-Dimensional Data | 0.1.2 | 0.1.2 |
sparsebnUtils Utilities for Learning Sparse Bayesian Networks | 0.0.8 | 0.0.8 |
SparseFactorAnalysis Scaling Count and Binary Data with Sparse Factor Analysis | 1.0 | 1.0 |
sparseFLMM Functional Linear Mixed Models for Irregularly or Sparsely Sampled Data | 0.4.1 | 0.4.1 |
SparseGrid Sparse grid integration in R | 0.8.2 | 0.8.2 |
sparseinv Computation of the Sparse Inverse Subset | 0.1.3 | 0.1.3 |
SparseM Sparse Linear Algebra | 1.81 | 1.81 |
sparseMatrixStats | 1.8.0 | 1.8.0 |
sparseMVN Multivariate Normal Functions for Sparse Covariance and Precision Matrices | 0.2.2 | 0.2.2 |
sparseSEM Sparse-aware Maximum Likelihood for Structural Equation Models | 2.5 | 2.5 |
sparsevar Sparse VAR/VECM Models Estimation | 0.1.0 | 0.1.0 |
spate Spatio-Temporal Modeling of Large Data Using a Spectral SPDE Approach | 1.7 | 1.7 |
SPAtest Score Test and Meta-Analysis Based on Saddlepoint Approximation | 3.1.2 | 3.1.2 |
spatgraphs Graph Edge Computations for Spatial Point Patterns | 3.4 | 3.4 |
spatial Functions for Kriging and Point Pattern Analysis | 7.3-16 | 7.3-16 |
spatialCovariance Computation of Spatial Covariance Matrices for Data on Rectangles | 0.6-9 | 0.6-9 |
SpatialEpi Methods and Data for Spatial Epidemiology | 1.2.8 | 1.2.8 |
SpatialNP Multivariate Nonparametric Methods Based on Spatial Signs and Ranks | 1.1-5 | 1.1-5 |
SpatialPosition Spatial Position Models | 2.1.1 | 2.1.1 |
spatialprobit Spatial Probit Models | 0.9-11 | 0.9-11 |
spatialreg Spatial Regression Analysis | 1.1-8 | 1.1-8 |
spatialsegregation Segregation Measures for Multitype Spatial Point Patterns | 2.45 | 2.45 |
SpatialTools Tools for Spatial Data Analysis | 1.0.4 | 1.0.4 |
spatialwidget Formats Spatial Data for Use in Htmlwidgets | 0.2.3 | 0.2.3 |
SpaTimeClus Model-Based Clustering of Spatio-Temporal Data | 1.0.1 | 1.0.1 |
spatsoc Group Animal Relocation Data by Spatial and Temporal Relationship | 0.1.16 | 0.1.16 |
spatstat Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests | 3.0-3 | 3.0-3 |
spatstat.core Core Functionality of the 'spatstat' Family | 2.4-4 | 2.4-4 |
spatstat.data Datasets for 'spatstat' Family | 3.0-0 | 3.0-0 |
spatstat.explore Exploratory Data Analysis for the 'spatstat' Family | 3.0-6 | 3.0-6 |
spatstat.geom Geometrical Functionality of the 'spatstat' Family | 3.0-6 | 3.0-6 |
spatstat.linnet Linear Networks Functionality of the 'spatstat' Family | 3.0-6 | 3.0-6 |
spatstat.model Parametric Statistical Modelling and Inference for the 'spatstat' Family | 3.2-1 | 3.2-1 |
spatstat.random Random Generation Functionality for the 'spatstat' Family | 3.1-3 | 3.1-3 |
spatstat.sparse Sparse Three-Dimensional Arrays and Linear Algebra Utilities | 3.0-0 | 3.0-0 |
spatstat.utils Utility Functions for 'spatstat' | 2.3-1 | 2.3-1 |
spatsurv Bayesian Spatial Survival Analysis with Parametric Proportional Hazards Models | 1.5 | 1.5 |
spBayes Univariate and Multivariate Spatial-Temporal Modeling | 0.4-6 | 0.4-6 |
spBayesSurv Bayesian Modeling and Analysis of Spatially Correlated Survival Data | 1.1.6 | 1.1.6 |
spc Statistical Process Control -- Calculation of ARL and Other Control Chart Performance Measures | 0.6.5 | 0.6.5 |
spcosa Spatial Coverage Sampling and Random Sampling from Compact Geographical Strata | 0.4-0 | 0.4-0 |
spCP Spatially Varying Change Points | 1.2 | 1.2 |
spd Semi Parametric Distribution | 2.0-1 | 2.0-1 |
spData Datasets for Spatial Analysis | 2.2.2 | 2.2.2 |
spdep Spatial Dependence: Weighting Schemes, Statistics | 1.1-8 | 1.1-8 |
speaq Tools for Nuclear Magnetic Resonance (NMR) Spectra Alignment, Peak Based Processing, Quantitative Analysis and Visualizations | 2.7.0 | 2.7.0 |
spectral Common Methods of Spectral Data Analysis | 2.0 | 2.0 |
spectral.methods Singular Spectrum Analysis (SSA) Tools for Time Series Analysis | 0.7.2.133 | 0.7.2.133 |
spectralAnalysis Pre-Process, Visualize and Analyse Spectral Data | 3.12.0 | 3.12.0 |
Spectrum Fast Adaptive Spectral Clustering for Single and Multi-View Data | 1.1 | 1.1 |
speff2trial Semiparametric Efficient Estimation for a Two-Sample Treatment Effect | 1.0.5 | 1.0.5 |
SPEI Calculation of the Standardized Precipitation-Evapotranspiration Index | 1.8.1 | 1.8.1 |
spelling Tools for Spell Checking in R | 2.2 | 2.2 |
sperrorest Perform Spatial Error Estimation and Variable Importance Assessment | 3.0.5 | 3.0.5 |
spfrontier Spatial Stochastic Frontier Models | 0.2.5 | 0.2.5 |
spgrass6 Interface Between GRASS 6+ Geographical Information System and R | 0.8-9 | 0.8-9 |
spgwr Geographically Weighted Regression | 0.6-35 | 0.6-35 |
SphericalCubature Numerical Integration over Spheres and Balls in n-Dimensions; Multivariate Polar Coordinates | 1.5 | 1.5 |
sphet Estimation of Spatial Autoregressive Models with and without Heteroskedastic Innovations | 1.7 | 1.7 |
spiderbar Parse and Test Robots Exclusion Protocol Files and Rules | 0.2.5 | 0.2.5 |
spikeslab Prediction and Variable Selection Using Spike and Slab Regression | 1.1.6 | 1.1.6 |
spikeSlabGAM Bayesian Variable Selection and Model Choice for Generalized Additive Mixed Models | 1.1-19 | 1.1-19 |
spind Spatial Methods and Indices | 2.2.1 | 2.2.1 |
splancs Spatial and Space-Time Point Pattern Analysis | 2.01-43 | 2.01-43 |
splashr Tools to Work with the 'Splash' 'JavaScript' Rendering and Scraping Service | 0.6.0 | 0.6.0 |
| 4.2.3 | 4.2.3 | |
splines2 Regression Spline Functions and Classes | 0.4.7 | 0.4.7 |
splinetree Longitudinal Regression Trees and Forests | 0.2.0 | 0.2.0 |
splm Econometric Models for Spatial Panel Data | 1.4-11 | 1.4-11 |
spls Sparse Partial Least Squares (SPLS) Regression and Classification | 2.2-3 | 2.2-3 |
splus2R Supplemental S-PLUS Functionality in R | 1.3-3 | 1.3-3 |
splusTimeDate Times and Dates from S-PLUS | 2.5.4 | 2.5.4 |
splusTimeSeries Time Series from S-PLUS | 1.5.5 | 1.5.5 |
spm Spatial Predictive Modeling | 1.2.1 | 1.2.1 |
spmoran Fast Spatial Regression using Moran Eigenvectors | 0.2.1 | 0.2.1 |
spocc Interface to Species Occurrence Data Sources | 1.2.0 | 1.2.0 |
spray Sparse Arrays and Multivariate Polynomials | 1.0-19 | 1.0-19 |
spsann Optimization of Sample Configurations using Spatial Simulated Annealing | 2.2.0 | 2.2.0 |
spselect Selecting Spatial Scale of Covariates in Regression Models | 0.0.1 | 0.0.1 |
spsurvey Spatial Sampling Design and Analysis | 5.4.1 | 5.4.1 |
spThin Functions for Spatial Thinning of Species Occurrence Records for Use in Ecological Models | 0.2.0 | 0.2.0 |
spTimer Spatio-Temporal Bayesian Modelling | 3.3.2 | 3.3.2 |
sqldf Manipulate R Data Frames Using SQL | 0.4-11 | 0.4-11 |
SQUAREM Squared Extrapolation Methods for Accelerating EM-Like Monotone Algorithms | 2021.1 | 2021.1 |
srvyr 'dplyr'-Like Syntax for Summary Statistics of Survey Data | 1.2.0 | 1.2.0 |
ssanv Sample Size Adjusted for Nonadherence or Variability of Input Parameters | 1.1 | 1.1 |
SSBtools Statistics Norway's Miscellaneous Tools | 1.4.2 | 1.4.2 |
ssfa Spatial Stochastic Frontier Analysis | 1.1 | 1.1 |
ssgraph Bayesian Graph Structure Learning using Spike-and-Slab Priors | 1.14 | 1.14 |
ssh Secure Shell (SSH) Client for R | 0.8.2 | 0.8.2 |
ssize.fdr Sample Size Calculations for Microarray Experiments | 1.3 | 1.3 |
ssizeRNA Sample Size Calculation for RNA-Seq Experimental Design | 1.3.2 | 1.3.2 |
ssmrob Robust Estimation and Inference in Sample Selection Models | 1.0 | 1.0 |
SSN Spatial Modeling on Stream Networks | 1.1.17 | 1.1.17 |
SSRMST Sample Size Calculation using Restricted Mean Survival Time | 0.1.1 | 0.1.1 |
ssvd Sparse SVD | 1.0 | 1.0 |
ssym Fitting Semi-Parametric log-Symmetric Regression Models | 1.5.7 | 1.5.7 |
st Shrinkage t Statistic and Correlation-Adjusted t-Score | 1.2.7 | 1.2.7 |
stable Probability Functions and Generalized Regression Models for Stable Distributions | 1.1.6 | 1.1.6 |
stabledist Stable Distribution Functions | 0.7-1 | 0.7-1 |
stabs Stability Selection with Error Control | 0.6-4 | 0.6-4 |
stam Spatio-Temporal Analysis and Modelling | 0.0-1 | 0.0-1 |
StAMPP Statistical Analysis of Mixed Ploidy Populations | 1.6.3 | 1.6.3 |
stampr Spatial Temporal Analysis of Moving Polygons | 0.2 | 0.2 |
StanHeaders C++ Header Files for Stan | 2.21.0-7 | 2.21.0-7 |
STAR Spike Train Analysis with R | 0.3-7 | 0.3-7 |
stargazer Well-Formatted Regression and Summary Statistics Tables | 5.2.3 | 5.2.3 |
starma Modelling Space Time AutoRegressive Moving Average (STARMA) Processes | 1.3 | 1.3 |
stars Spatiotemporal Arrays, Raster and Vector Data Cubes | 0.5-3 | 0.5-3 |
STARTS Functions for the STARTS Model | 1.3-8 | 1.3-8 |
startupmsg Utilities for Start-Up Messages | 0.9.6 | 0.9.6 |
statebins Create United States Uniform Cartogram Heatmaps | 1.4.0 | 1.4.0 |
stationaRy Detailed Meteorological Data from Stations All Over the World | 0.5.1 | 0.5.1 |
statip Statistical Functions for Probability Distributions and Regression | 0.2.3 | 0.2.3 |
StatMatch Statistical Matching or Data Fusion | 1.4.1 | 1.4.1 |
statmod Statistical Modeling | 1.4.37 | 1.4.37 |
statnet Software Tools for the Statistical Analysis of Network Data | 2019.6 | 2019.6 |
statnet.common Common R Scripts and Utilities Used by the Statnet Project Software | 4.8.0 | 4.8.0 |
StatRank Statistical Rank Aggregation: Inference, Evaluation, and Visualization | 0.0.6 | 0.0.6 |
stats | 4.2.3 | 4.2.3 |
stats19 Work with Open Road Traffic Casualty Data from Great Britain | 2.0.0 | 2.0.0 |
stats4 | 4.2.3 | 4.2.3 |
steadyICA ICA and Tests of Independence via Multivariate Distance Covariance | 1.0 | 1.0 |
stellaR Evolutionary Tracks and Isochrones from Pisa Stellar Evolution Database | 0.3-4 | 0.3-4 |
Stem Spatio-temporal models in R | 1.0 | 1.0 |
StempCens Spatio-Temporal Estimation and Prediction for Censored/Missing Responses | 1.1.0 | 1.1.0 |
stepPlr L2 Penalized Logistic Regression with Stepwise Variable Selection | 0.93 | 0.93 |
stevedore Docker Client | 0.9.4 | 0.9.4 |
stinepack Stineman, a Consistently Well Behaved Method of Interpolation | 1.4 | 1.4 |
stlplus Enhanced Seasonal Decomposition of Time Series by Loess | 0.5.1 | 0.5.1 |
stm Estimation of the Structural Topic Model | 1.3.6 | 1.3.6 |
STMedianPolish Spatio-Temporal Median Polish | 0.2 | 0.2 |
stochvol Efficient Bayesian Inference for Stochastic Volatility (SV) Models | 3.2.1 | 3.2.1 |
stopwords Multilingual Stopword Lists | 2.3 | 2.3 |
storr Simple Key Value Stores | 1.2.5 | 1.2.5 |
stplanr Sustainable Transport Planning | 0.8.3 | 0.8.3 |
stR STR Decomposition | 0.5 | 0.5 |
strap Stratigraphic Tree Analysis for Palaeontology | 1.6-0 | 1.6-0 |
stratification Univariate Stratification of Survey Populations | 2.2-7 | 2.2-7 |
StratifiedRF Builds Trees by Sampling Variables in Groups | 0.2.2 | 0.2.2 |
StreamMetabolism Calculate Single Station Metabolism from Diurnal Oxygen Curves | 1.1.2 | 1.1.2 |
streamR Access to Twitter Streaming API via R | 0.4.5 | 0.4.5 |
stringdist Approximate String Matching, Fuzzy Text Search, and String Distance Functions | 0.9.10 | 0.9.10 |
stringfish Alt String Implementation | 0.15.7 | 0.15.7 |
stringi Fast and Portable Character String Processing Facilities | 1.7.12 | 1.7.12 |
stringr Simple, Consistent Wrappers for Common String Operations | 1.4.1 | 1.4.1 |
strucchange Testing, Monitoring, and Dating Structural Changes | 1.5-3 | 1.5-3 |
strucchangeRcpp Testing, Monitoring, and Dating Structural Changes: C++ Version | 1.5-3-1.0.4 | 1.5-3-1.0.4 |
stsm Structural Time Series Models | 1.9 | 1.9 |
stsm.class Class and Methods for Structural Time Series Models | 1.3 | 1.3 |
styler Non-Invasive Pretty Printing of R Code | 1.7.0 | 1.7.0 |
subplex Unconstrained Optimization using the Subplex Algorithm | 1.8 | 1.8 |
subscore Computing Subscores in Classical Test Theory and Item Response Theory | 3.3 | 3.3 |
sugrrants Supporting Graphs for Analysing Time Series | 0.2.8 | 0.2.8 |
SummarizedExperiment | 1.26.1 | 1.26.1 |
suncalc Compute Sun Position, Sunlight Phases, Moon Position and Lunar Phase | 0.5.0 | 0.5.0 |
sundialr An Interface to 'SUNDIALS' Ordinary Differential Equation (ODE) Solvers | 0.1.4.1 | 0.1.4.1 |
SuperLearner Super Learner Prediction | 2.0-28 | 2.0-28 |
superMDS Implements the supervised multidimensional scaling (superMDS) proposal of Witten and Tibshirani (2011) | 1.0.2 | 1.0.2 |
superpc Supervised Principal Components | 1.12 | 1.12 |
SuppDists Supplementary Distributions | 1.1-9.7 | 1.1-9.7 |
suRtex LaTeX descriptive statistic reporting for survey data | 0.9 | 0.9 |
surv2sampleComp Inference for Model-Free Between-Group Parameters for Censored Survival Data | 1.0-5 | 1.0-5 |
survC1 C-Statistics for Risk Prediction Models with Censored Survival Data | 1.0-3 | 1.0-3 |
survcomp Performance Assessment and Comparison for Survival Analysis | 1.46.0 | 1.46.0 |
SurvCorr Correlation of Bivariate Survival Times | 1.1 | 1.1 |
surveillance Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena | 1.21.0 | 1.21.0 |
survexp.fr Relative Survival, AER and SMR Based on French Death Rates | 1.1 | 1.1 |
survey Analysis of Complex Survey Samples | 4.1-1 | 4.1-1 |
surveybootstrap Bootstrap with Survey Data | 0.0.3 | 0.0.3 |
surveydata Tools to Work with Survey Data | 0.2.7 | 0.2.7 |
surveyoutliers Helps Manage Outliers in Sample Surveys | 0.1 | 0.1 |
surveyplanning Survey Planning Tools | 4.0 | 4.0 |
Survgini The Gini concentration test for survival data | 1.0 | 1.0 |
survIDINRI IDI and NRI for Comparing Competing Risk Prediction Models with Censored Survival Data | 1.1-2 | 1.1-2 |
survival Survival Analysis | 3.3-1 | 3.3-1 |
survivalMPL Penalised Maximum Likelihood for Survival Analysis Models | 0.2-3 | 0.2-3 |
survivalROC Time-Dependent ROC Curve Estimation from Censored Survival Data | 1.0.3.1 | 1.0.3.1 |
survJamda Survival Prediction by Joint Analysis of Microarray Gene Expression Data | 1.1.4 | 1.1.4 |
survJamda.data Data for Package 'survJambda' | 1.0.2 | 1.0.2 |
SurvLong Analysis of Proportional Hazards Model with Sparse Longitudinal Covariates | 1.2 | 1.2 |
survminer Drawing Survival Curves using 'ggplot2' | 0.4.9 | 0.4.9 |
survMisc Miscellaneous Functions for Survival Data | 0.5.6 | 0.5.6 |
survPresmooth Presmoothed Estimation in Survival Analysis | 1.1-11 | 1.1-11 |
SurvRegCensCov Weibull Regression for a Right-Censored Endpoint with Interval-Censored Covariate | 1.5 | 1.5 |
survRM2 Comparing Restricted Mean Survival Time | 1.0-4 | 1.0-4 |
survsim Simulation of Simple and Complex Survival Data | 1.1.8 | 1.1.8 |
survSNP Power Calculations for SNP Studies with Censored Outcomes | 0.26 | 0.26 |
sva | 3.44.0 | 3.44.0 |
svars Data-Driven Identification of SVAR Models | 1.3.11 | 1.3.11 |
svd Interfaces to Various State-of-Art SVD and Eigensolvers | 0.5.4 | 0.5.4 |
svglite An 'SVG' Graphics Device | 2.1.1 | 2.1.1 |
svgPanZoom R 'Htmlwidget' to Add Pan and Zoom to Almost any R Graphic | 0.3.4 | 0.3.4 |
svmpath The SVM Path Algorithm | 0.970 | 0.970 |
SvyNom Nomograms for Right-Censored Outcomes from Survey Designs | 1.2 | 1.2 |
svyPVpack A package for complex surveys including plausible values | 0.1-1 | 0.1-1 |
swagger Dynamically Generates Documentation from a 'Swagger' Compliant API | 3.33.1 | 3.33.1 |
sweep Tidy Tools for Forecasting | 0.2.3 | 0.2.3 |
swgee Simulation Extrapolation Inverse Probability Weighted Generalized Estimating Equations | 1.4 | 1.4 |
swirl Learn R, in R | 2.4.5 | 2.4.5 |
switchnpreg Switching nonparametric regression models for a single curve and functional data | 0.8-0 | 0.8-0 |
swmmr R Interface for US EPA's SWMM | 0.9.1 | 0.9.1 |
sylly Hyphenation and Syllable Counting for Text Analysis | 0.1-6 | 0.1-6 |
sym.arma Autoregressive and Moving Average Symmetric Models | 1.0 | 1.0 |
symengine Interface to the 'SymEngine' Library | 0.2.2 | 0.2.2 |
symmoments Symbolic Central and Noncentral Moments of the Multivariate Normal Distribution | 1.2.1 | 1.2.1 |
SYNCSA Analysis of Functional and Phylogenetic Patterns in Metacommunities | 1.3.4 | 1.3.4 |
synthpop Generating Synthetic Versions of Sensitive Microdata for Statistical Disclosure Control | 1.8-0 | 1.8-0 |
sys Powerful and Reliable Tools for Running System Commands in R | 3.4.1 | 3.4.1 |
sysfonts Loading Fonts into R | 0.8.8 | 0.8.8 |
systemfit Estimating Systems of Simultaneous Equations | 1.1-28 | 1.1-28 |
systemfonts System Native Font Finding | 1.0.4 | 1.0.4 |
tab Create Summary Tables for Statistical Reports | 5.1.1 | 5.1.1 |
tableone Create 'Table 1' to Describe Baseline Characteristics with or without Propensity Score Weights | 0.13.2 | 0.13.2 |
tables Formula-Driven Table Generation | 0.9.10 | 0.9.10 |
tabuSearch Tabu Search Algorithm for Binary Configurations | 1.1.1 | 1.1.1 |
tagcloud Tag Clouds | 0.6 | 0.6 |
TAM Test Analysis Modules | 4.1-4 | 4.1-4 |
TAQMNGR Manage Tick-by-Tick Transaction Data | 2018.5-1 | 2018.5-1 |
TAR Bayesian Modeling of Autoregressive Threshold Time Series Models | 1.0 | 1.0 |
taRifx Collection of Utility and Convenience Functions | 1.0.6.2 | 1.0.6.2 |
tau Text Analysis Utilities | 0.0-24 | 0.0-24 |
taxize Taxonomic Information from Around the Web | 0.9.100 | 0.9.100 |
tbart Teitz and Bart's p-Median Algorithm | 1.0 | 1.0 |
tbrf Time-Based Rolling Functions | 0.1.5 | 0.1.5 |
TBSSurvival Survival Analysis using a Transform-Both-Sides Model | 1.3 | 1.3 |
tcltk Basic interface with tcl/tk | 4.2.3 | 4.2.3 |
tcltk2 Tcl/Tk Additions | 1.2-11 | 1.2-11 |
tclust Robust Trimmed Clustering | 1.5-1 | 1.5-1 |
Tcomp Data from the 2010 Tourism Forecasting Competition | 1.0.1 | 1.0.1 |
TDA Statistical Tools for Topological Data Analysis | 1.8.7 | 1.8.7 |
TDAmapper Analyze High-Dimensional Data Using Discrete Morse Theory | 1.0 | 1.0 |
TDAstats Pipeline for Topological Data Analysis | 0.4.1 | 0.4.1 |
tdigest Wicked Fast, Accurate Quantiles Using t-Digests | 0.4.1 | 0.4.1 |
tdROC Nonparametric Estimation of Time-Dependent ROC Curve from Right Censored Survival Data | 1.0 | 1.0 |
tdthap TDT Tests for Extended Haplotypes | 1.1-11 | 1.1-11 |
tea Threshold Estimation Approaches | 1.1 | 1.1 |
TeachingDemos Demonstrations for Teaching and Learning | 2.12 | 2.12 |
teigen Model-Based Clustering and Classification with the Multivariate t Distribution | 2.2.2 | 2.2.2 |
telegram R Wrapper Around the Telegram Bot API | 0.6.0 | 0.6.0 |
tempdisagg Methods for Temporal Disaggregation and Interpolation of Time Series | 1.0 | 1.0 |
tensor Tensor product of arrays | 1.5 | 1.5 |
tensorA Advanced Tensor Arithmetic with Named Indices | 0.36.2 | 0.36.2 |
tensorBF Bayesian Tensor Factorization | 1.0.2 | 1.0.2 |
tensorflow R Interface to 'TensorFlow' | 2.9.0 | 2.9.0 |
TEQR Target Equivalence Range Design | 6.0-0 | 6.0-0 |
tergm Fit, Simulate and Diagnose Models for Network Evolution Based on Exponential-Family Random Graph Models | 4.1.1 | 4.1.1 |
term Create, Manipulate and Query Parameter Terms | 0.3.4 | 0.3.4 |
terra Spatial Data Analysis | 1.1-4 | 1.1-4 |
TESS Diversification Rate Estimation and Fast Simulation of Reconstructed Phylogenetic Trees under Tree-Wide Time-Heterogeneous Birth-Death Processes Including Mass-Extinction Events | 2.1.2 | 2.1.2 |
tesseract Open Source OCR Engine | 5.1.0 | 5.1.0 |
TestDataImputation Missing Item Responses Imputation for Test and Assessment Data | 2.3 | 2.3 |
tester Tests and checks characteristics of R objects | 0.1.7 | 0.1.7 |
testit A Simple Package for Testing R Packages | 0.13 | 0.13 |
TestScorer GUI for Entering Test Items and Obtaining Raw and Transformed Scores | 1.7.2 | 1.7.2 |
testthat Unit Testing for R | 3.1.7 | 3.1.7 |
TexExamRandomizer Personalizes and Randomizes Exams Written in 'LaTeX' | 1.2.3 | 1.2.3 |
texPreview Compile and Preview Snippets of 'LaTeX' | 2.0.0 | 2.0.0 |
texreg Conversion of R Regression Output to LaTeX or HTML Tables | 1.38.6 | 1.38.6 |
text2vec Modern Text Mining Framework for R | 0.6.3 | 0.6.3 |
textcat N-Gram Based Text Categorization | 1.0-8 | 1.0-8 |
textir Inverse Regression for Text Analysis | 2.0-5 | 2.0-5 |
textrank Summarize Text by Ranking Sentences and Finding Keywords | 0.3.1 | 0.3.1 |
textreuse Detect Text Reuse and Document Similarity | 0.1.5 | 0.1.5 |
textshaping Bindings to the 'HarfBuzz' and 'Fribidi' Libraries for Text Shaping | 0.3.6 | 0.3.6 |
tfautograph Autograph R for 'Tensorflow' | 0.3.2 | 0.3.2 |
tfdatasets Interface to 'TensorFlow' Datasets | 2.7.0 | 2.7.0 |
tfdeploy Deploy 'TensorFlow' Models | 0.6.1 | 0.6.1 |
tfestimators Interface to 'TensorFlow' Estimators | 1.9.2 | 1.9.2 |
TFisher Optimal Thresholding Fisher's P-Value Combination Method | 0.2.0 | 0.2.0 |
TFMPvalue Efficient and Accurate P-Value Computation for Position Weight Matrices | 0.0.8 | 0.0.8 |
tfplot Time Frame User Utilities | 2021.6-1 | 2021.6-1 |
tframe Time Frame Coding Kernel | 2015.12-1.1 | 2015.12-1.1 |
tfruns Training Run Tools for 'TensorFlow' | 1.5.1 | 1.5.1 |
TFX R API to TrueFX(tm) | 0.1.0 | 0.1.0 |
tgp Bayesian Treed Gaussian Process Models | 2.4-20 | 2.4-20 |
TH.data TH's Data Archive | 1.1-1 | 1.1-1 |
thief Temporal Hierarchical Forecasting | 0.3 | 0.3 |
ThreeArmedTrials Design and Analysis of Clinical Non-Inferiority or Superiority Trials with Active and Placebo Control | 1.0-3 | 1.0-3 |
ThreeGroups ML Estimator for Baseline-Placebo-Treatment (Three-Group) Experiments | 0.21 | 0.21 |
threejs Interactive 3D Scatter Plots, Networks and Globes | 0.3.3 | 0.3.3 |
ThreeWay Three-Way Component Analysis | 1.1.3 | 1.1.3 |
threewords Represent Precise Coordinates in Three Words | 0.1.0 | 0.1.0 |
thregI Threshold Regression for Interval-Censored Data with a Cure Rate Option | 1.0.4 | 1.0.4 |
threshr Threshold Selection and Uncertainty for Extreme Value Analysis | 1.0.3 | 1.0.3 |
tibble Simple Data Frames | 3.2.0 | 3.2.0 |
tibbletime Time Aware Tibbles | 0.1.8 | 0.1.8 |
tictoc Functions for Timing R Scripts, as Well as Implementations of "Stack" and "List" Structures | 1.1 | 1.1 |
Tides Quasi-Periodic Time Series Characteristics | 2.1 | 2.1 |
tidycensus Load US Census Boundary and Attribute Data as 'tidyverse' and 'sf'-Ready Data Frames | 1.2.1 | 1.2.1 |
tidygraph A Tidy API for Graph Manipulation | 1.2.3 | 1.2.3 |
tidyhydat Extract and Tidy Canadian 'Hydrometric' Data | 0.5.9 | 0.5.9 |
tidymodels Easily Install and Load the 'Tidymodels' Packages | 0.2.0 | 0.2.0 |
tidypredict Run Predictions Inside the Database | 0.5 | 0.5 |
tidyquant Tidy Quantitative Financial Analysis | 1.0.6 | 1.0.6 |
tidyqwi A Convenient API for Accessing United States Census Bureau's Quarterly Workforce Indicator | 0.1.2 | 0.1.2 |
tidyr Tidy Messy Data | 1.3.0 | 1.3.0 |
tidyRSS Tidy RSS for R | 2.0.7 | 2.0.7 |
tidyselect Select from a Set of Strings | 1.2.0 | 1.2.0 |
tidytext Text Mining using 'dplyr', 'ggplot2', and Other Tidy Tools | 0.4.1 | 0.4.1 |
tidytransit Read, Validate, Analyze, and Map GTFS Feeds | 1.3.0 | 1.3.0 |
tidytree A Tidy Tool for Phylogenetic Tree Data Manipulation | 0.3.9 | 0.3.9 |
tidyverse Easily Install and Load the 'Tidyverse' | 1.3.1 | 1.3.1 |
tiger TIme series of Grouped ERrors | 0.2.3.1 | 0.2.3.1 |
tigris Load Census TIGER/Line Shapefiles | 1.6 | 1.6 |
tiler Create Geographic and Non-Geographic Map Tiles | 0.2.5 | 0.2.5 |
timechange Efficient Manipulation of Date-Times | 0.2.0 | 0.2.0 |
timeDate Rmetrics - Chronological and Calendar Objects | 4021.106 | 4021.106 |
TimeProjection Time Projections | 0.2.0 | 0.2.0 |
timereg Flexible Regression Models for Survival Data | 2.0.5 | 2.0.5 |
timeROC Time-Dependent ROC Curve and AUC for Censored Survival Data | 0.4 | 0.4 |
timesboot Bootstrap computations for time series objects | 1.0 | 1.0 |
timeSeries Financial Time Series Objects (Rmetrics) | 4021.105 | 4021.105 |
timeseriesdb A Time Series Database for Official Statistics with R and PostgreSQL | 1.0.0-1.1.2 | 1.0.0-1.1.2 |
timetk A Tool Kit for Working with Time Series | 2.8.2 | 2.8.2 |
TIMP Fitting Separable Nonlinear Models in Spectroscopy and Microscopy | 1.13.2 | 1.13.2 |
timsac Time Series Analysis and Control Package | 1.3.8 | 1.3.8 |
tinyProject A Lightweight Template for Data Analysis Projects | 0.6.1 | 0.6.1 |
tinytest Lightweight and Feature Complete Unit Testing Framework | 1.4.1 | 1.4.1 |
tinytex Helper Functions to Install and Maintain TeX Live, and Compile LaTeX Documents | 0.44 | 0.44 |
tis Time Indexes and Time Indexed Series | 1.39 | 1.39 |
titan Titration analysis for mass spectrometry data | 1.0-16 | 1.0-16 |
titrationCurves Acid/Base, Complexation, Redox, and Precipitation Titration Curves | 0.1.0 | 0.1.0 |
tkrplot TK Rplot | 0.0-26 | 0.0-26 |
tlmec Linear Student-t Mixed-Effects Models with Censored Data | 0.0-2 | 0.0-2 |
TLMoments Calculate TL-Moments and Convert Them to Distribution Parameters | 0.7.5.3 | 0.7.5.3 |
tlrmvnmvt Low-Rank Methods for MVN and MVT Probabilities | 1.1.2 | 1.1.2 |
tm Text Mining Package | 0.7-11 | 0.7-11 |
tm.plugin.alceste Import texts from files in the Alceste format using the tm text<U+000a>mining framework | 1.1 | 1.1 |
tm.plugin.dc Text Mining Distributed Corpus Plug-in | 0.2-10 | 0.2-10 |
tm.plugin.europresse Import Articles from 'Europresse' Using the 'tm' Text Mining Framework | 1.4 | 1.4 |
tm.plugin.factiva Import Articles from 'Factiva' Using the 'tm' Text Mining Framework | 1.8 | 1.8 |
tm.plugin.lexisnexis Import Articles from 'LexisNexis' Using the 'tm' Text Mining Framework | 1.4.1 | 1.4.1 |
tm.plugin.mail Text Mining E-Mail Plug-in | 0.2-2 | 0.2-2 |
tm.plugin.webmining Retrieve Structured, Textual Data from Various Web Sources | 1.3 | 1.3 |
tmap Thematic Maps | 3.3-2 | 3.3-2 |
tmaptools Thematic Map Tools | 3.1-1 | 3.1-1 |
TMB Template Model Builder: A General Random Effect Tool Inspired by 'ADMB' | 1.8.1 | 1.8.1 |
tmvmixnorm Sampling from Truncated Multivariate Normal and t Distributions | 1.1.1 | 1.1.1 |
tmvtnorm Truncated Multivariate Normal and Student t Distribution | 1.5 | 1.5 |
tokenizers Fast, Consistent Tokenization of Natural Language Text | 0.3.0 | 0.3.0 |
tokenizers.bpe Byte Pair Encoding Text Tokenization | 0.1.1 | 0.1.1 |
tolerance Statistical Tolerance Intervals and Regions | 2.0.0 | 2.0.0 |
tools | 4.2.3 | 4.2.3 |
topicdoc Topic-Specific Diagnostics for LDA and CTM Topic Models | 0.1.0 | 0.1.0 |
topicmodels Topic Models | 0.2-13 | 0.2-13 |
topmodel Implementation of the Hydrological Model TOPMODEL in R | 0.7.4 | 0.7.4 |
TP.idm Estimation of Transition Probabilities for the Illness-Death Model | 1.5 | 1.5 |
TPmsm Estimation of Transition Probabilities in Multistate Models | 1.2.7 | 1.2.7 |
tpr Temporal Process Regression | 0.3-3 | 0.3-3 |
trackdem Particle Tracking and Demography | 0.6 | 0.6 |
trackdf Data Frame Class for Tracking Data | 0.3.1 | 0.3.1 |
trackeR Infrastructure for Running, Cycling and Swimming Data from GPS-Enabled Tracking Devices | 1.5.2 | 1.5.2 |
TrackReconstruction Reconstruct Animal Tracks from Magnetometer, Accelerometer, Depth and Optional Speed Data | 1.3 | 1.3 |
tractor.base Read, Manipulate and Visualise Magnetic Resonance Images | 3.3.5.1 | 3.3.5.1 |
trade Tools for Trade Practitioners | 0.8.0 | 0.8.0 |
trafo Estimation, Comparison and Selection of Transformations | 1.0.1 | 1.0.1 |
traipse Shared Tools for Tracking Data | 0.3.0 | 0.3.0 |
TrajDataMining Trajectories Data Mining | 0.1.6 | 0.1.6 |
trajectories Classes and Methods for Trajectory Data | 0.2-6 | 0.2-6 |
trajr Animal Trajectory Analysis | 1.4.0 | 1.4.0 |
tram Transformation Models | 0.8-1 | 0.8-1 |
TraMineR Trajectory Miner: a Toolbox for Exploring and Rendering Sequences | 2.2-6 | 2.2-6 |
transcribeR Automated Transcription of Audio Files Through the HP IDOL API | 0.0.0 | 0.0.0 |
translate Bindings for the Google Translate API v2 | 0.1.2 | 0.1.2 |
translateR Bindings for the Google and Microsoft Translation APIs | 1.0 | 1.0 |
TransModel Fit Linear Transformation Models for Right Censored Data | 2.3 | 2.3 |
trapezoid The Trapezoidal Distribution | 2.0-2 | 2.0-2 |
tree Classification and Regression Trees | 1.0-43 | 1.0-43 |
treebase Discovery, Access and Manipulation of 'TreeBASE' Phylogenies | 0.1.4 | 0.1.4 |
TreeBUGS Hierarchical Multinomial Processing Tree Modeling | 1.4.9 | 1.4.9 |
treeClust Cluster Distances Through Trees | 1.1-7 | 1.1-7 |
treedater Fast Molecular Clock Dating of Phylogenetic Trees with Rate Variation | 0.5.0 | 0.5.0 |
treemap Treemap Visualization | 2.4-3 | 2.4-3 |
TreePar Estimating birth and death rates based on phylogenies | 3.3 | 3.3 |
TreeSim Simulating Phylogenetic Trees | 2.4 | 2.4 |
treespace Statistical Exploration of Landscapes of Phylogenetic Trees | 1.1.4.1 | 1.1.4.1 |
trekfont Star Trek Fonts Collection | 0.9.5 | 0.9.5 |
trelloR Access the Trello API | 0.7.1 | 0.7.1 |
trend Non-Parametric Trend Tests and Change-Point Detection | 1.1.4 | 1.1.4 |
TrialSize R Functions for Chapter 3,4,6,7,9,10,11,12,14,15 of Sample Size Calculation in Clinical Research | 1.4 | 1.4 |
triangle Distribution Functions and Parameter Estimates for the Triangle Distribution | 0.12 | 0.12 |
triebeard 'Radix' Trees in 'Rcpp' | 0.4.1 | 0.4.1 |
trimcluster Cluster Analysis with Trimming | 0.1-5 | 0.1-5 |
trip Tracking Data | 1.8.7 | 1.8.7 |
tripack Triangulation of Irregularly Spaced Data | 1.3-9.1 | 1.3-9.1 |
tripEstimation Metropolis Sampler and Supporting Functions for Estimating Animal Movement from Archival Tags and Satellite Fixes | 0.0-44 | 0.0-44 |
TripleR Social Relation Model (SRM) Analyses for Single or Multiple Groups | 1.5.4 | 1.5.4 |
tropicalSparse Sparse Tropical Algebra | 0.1.0 | 0.1.0 |
trtf Transformation Trees and Forests | 0.4-2 | 0.4-2 |
truncdist Truncated Random Variables | 1.0-2 | 1.0-2 |
truncnorm Truncated Normal Distribution | 1.0-9 | 1.0-9 |
truncreg Truncated Gaussian Regression Models | 0.2-5 | 0.2-5 |
trust Trust Region Optimization | 0.1-8 | 0.1-8 |
TSA Time Series Analysis | 1.3.1 | 1.3.1 |
tsallisqexp Tsallis q-Exp Distribution | 0.9-4 | 0.9-4 |
tsbox Class-Agnostic Time Series | 0.4 | 0.4 |
TSclust Time Series Clustering Utilities | 1.3.1 | 1.3.1 |
TScompare 'TSdbi' Database Comparison | 2015.4-1 | 2015.4-1 |
tscount Analysis of Count Time Series | 1.4.3 | 1.4.3 |
TSdbi Time Series Database Interface | 2017.4-1 | 2017.4-1 |
tsdecomp Decomposition of Time Series Data | 0.2 | 0.2 |
tsdisagg2 Time Series Disaggregation | 0.1.0 | 0.1.0 |
TSdist Distance Measures for Time Series Data | 3.7.1 | 3.7.1 |
tsDyn Nonlinear Time Series Models with Regime Switching | 11.0.2 | 11.0.2 |
TSEntropies Time Series Entropies | 0.9 | 0.9 |
tseries Time Series Analysis and Computational Finance | 0.10-53 | 0.10-53 |
tseriesChaos Analysis of Nonlinear Time Series | 0.1-13.1 | 0.1-13.1 |
tseriesEntropy Entropy Based Analysis and Tests for Time Series | 0.6-0 | 0.6-0 |
tsfa Time Series Factor Analysis | 2021.1-3 | 2021.1-3 |
tsfeatures Time Series Feature Extraction | 1.1 | 1.1 |
tsfknn Time Series Forecasting Using Nearest Neighbors | 0.5.1 | 0.5.1 |
TSHRC Two Stage Hazard Rate Comparison | 0.1-6 | 0.1-6 |
tsibble Tidy Temporal Data Frames and Tools | 1.1.3 | 1.1.3 |
tsibbledata Diverse Datasets for 'tsibble' | 0.4.1 | 0.4.1 |
tsintermittent Intermittent Time Series Forecasting | 1.9 | 1.9 |
TSMining Mining Univariate and Multivariate Motifs in Time-Series Data | 1.0 | 1.0 |
tsModel Time Series Modeling for Air Pollution and Health | 0.6-1 | 0.6-1 |
tsna Tools for Temporal Social Network Analysis | 0.3.5 | 0.3.5 |
tsne T-Distributed Stochastic Neighbor Embedding for R (t-SNE) | 0.1-3.1 | 0.1-3.1 |
tsoutliers Detection of Outliers in Time Series | 0.6-8 | 0.6-8 |
TSP Traveling Salesperson Problem (TSP) | 1.2-3 | 1.2-3 |
tsPI Improved Prediction Intervals for ARIMA Processes and Structural Time Series | 1.0.3 | 1.0.3 |
TSrepr Time Series Representations | 1.1.0 | 1.1.0 |
TSstudio Functions for Time Series Analysis and Forecasting | 0.1.6 | 0.1.6 |
tstools A Time Series Toolbox for Official Statistics | 0.4.1 | 0.4.1 |
TSTutorial Fitting and Predict Time Series Interactive Laboratory | 1.2.4 | 1.2.4 |
tsutils Time Series Exploration, Modelling and Forecasting | 0.9.2 | 0.9.2 |
tswge Time Series for Data Science | 2.1.0 | 2.1.0 |
TTmoment Sampling and Calculating the First and Second Moments for the Doubly Truncated Multivariate t Distribution | 1.0 | 1.0 |
TTR Technical Trading Rules | 0.24.3 | 0.24.3 |
tuber Client for the YouTube API | 0.9.9 | 0.9.9 |
tubern R Client for the YouTube Analytics and Reporting API | 0.1.0 | 0.1.0 |
tufte Tufte's Styles for R Markdown Documents | 0.12 | 0.12 |
tufterhandout Tufte-style html document format for rmarkdown | 1.2.1 | 1.2.1 |
tumblR Access to Tumblr V2 API | 1.2 | 1.2 |
tune Tidy Tuning Tools | 0.2.0 | 0.2.0 |
tuneR Analysis of Music and Speech | 1.4.3 | 1.4.3 |
turboEM A Suite of Convergence Acceleration Schemes for EM, MM and Other Fixed-Point Algorithms | 2021.1 | 2021.1 |
turner Turn vectors and lists of vectors into indexed structures | 0.1.7 | 0.1.7 |
TUWmodel Lumped/Semi-Distributed Hydrological Model for Education Purposes | 1.1-1 | 1.1-1 |
tvm Time Value of Money Functions | 0.5.1 | 0.5.1 |
tweedie Evaluation of Tweedie Exponential Family Models | 2.3.5 | 2.3.5 |
tweenr Interpolate Data for Smooth Animations | 2.0.2 | 2.0.2 |
tweet2r Twitter Collector for R and Export to 'SQLite', 'postGIS' and 'GIS' Format | 1.1 | 1.1 |
twitteR R Based Twitter Client | 1.1.9 | 1.1.9 |
TxDb.Hsapiens.UCSC.hg19.knownGene | 3.2.2 | 3.2.2 |
tximeta | 1.14.0 | 1.14.0 |
tximport | 1.24.0 | 1.24.0 |
txtq A Small Message Queue for Parallel Processes | 0.2.4 | 0.2.4 |
tzdb Time Zone Database Information | 0.3.0 | 0.3.0 |
ucminf General-Purpose Unconstrained Non-Linear Optimization | 1.1-4.1 | 1.1-4.1 |
udapi Urban Dictionary API Client | 0.1.3 | 0.1.3 |
udpipe Tokenization, Parts of Speech Tagging, Lemmatization and Dependency Parsing with the 'UDPipe' 'NLP' Toolkit | 0.8.11 | 0.8.11 |
udunits2 Udunits-2 Bindings for R | 0.13.2.1 | 0.13.2.1 |
ui Uncertainty Intervals and Sensitivity Analysis for Missing Data | 0.1.1 | 0.1.1 |
umap Uniform Manifold Approximation and Projection | 0.2.8.0 | 0.2.8.0 |
uniah Unimodal Additive Hazards Model | 1.1 | 1.1 |
uniReg Unimodal Penalized Spline Regression using B-Splines | 1.1 | 1.1 |
unisensR Read 'Unisens' Data | 0.3.3 | 0.3.3 |
unitizer Interactive R Unit Tests | 1.4.17 | 1.4.17 |
units Measurement Units for R Vectors | 0.8-0 | 0.8-0 |
universals S3 Generics for Bayesian Analyses | 0.0.5 | 0.0.5 |
univOutl Detection of Univariate Outliers | 0.4 | 0.4 |
UnivRNG Univariate Pseudo-Random Number Generation | 1.2.3 | 1.2.3 |
unmarked Models for Data from Unmarked Animals | 1.2.5 | 1.2.5 |
untb Ecological Drift under the UNTB | 1.7-4 | 1.7-4 |
updog Flexible Genotyping for Polyploids | 2.1.2 | 2.1.2 |
UPMASK Unsupervised Photometric Membership Assignment in Stellar Clusters | 1.2 | 1.2 |
UpSetR A More Scalable Alternative to Venn and Euler Diagrams for Visualizing Intersecting Sets | 1.4.0 | 1.4.0 |
uptasticsearch Get Data Frame Representations of 'Elasticsearch' Results | 0.4.0 | 0.4.0 |
urca Unit Root and Cointegration Tests for Time Series Data | 1.3-3 | 1.3-3 |
urlshorteneR R Wrapper for the 'Bit.ly' and 'Is.gd'/'v.gd' URL Shortening Services | 1.5.7 | 1.5.7 |
urltools Vectorised Tools for URL Handling and Parsing | 1.7.3 | 1.7.3 |
uroot Unit Root Tests for Seasonal Time Series | 2.1-2 | 2.1-2 |
USAboundaries Historical and Contemporary Boundaries of the United States of America | 0.4.0 | 0.4.0 |
UScensus2000cdp US Census 2000 Designated Places Shapefiles and Additional Demographic Data | 0.03 | 0.03 |
UScensus2000tract US Census 2000 Tract Level Shapefiles and Additional Demographic Data | 0.03 | 0.03 |
usdata Data on the States and Counties of the United States | 0.2.0 | 0.2.0 |
useful A Collection of Handy, Useful Functions | 1.2.6 | 1.2.6 |
usethis Automate Package and Project Setup | 2.1.6 | 2.1.6 |
UsingR Data Sets, Etc. for the Text "Using R for Introductory Statistics", Second Edition | 2.0-7 | 2.0-7 |
utf8 Unicode Text Processing | 1.2.3 | 1.2.3 |
utility Construct, Evaluate and Plot Value and Utility Functions | 1.4.5 | 1.4.5 |
utils | 4.2.3 | 4.2.3 |
uuid Tools for Generating and Handling of UUIDs | 1.1-0 | 1.1-0 |
uwot The Uniform Manifold Approximation and Projection (UMAP) Method for Dimensionality Reduction | 0.1.11 | 0.1.11 |
V8 Embedded JavaScript and WebAssembly Engine for R | 4.2.2 | 4.2.2 |
validate Data Validation Infrastructure | 1.1.1 | 1.1.1 |
validatetools Checking and Simplifying Validation Rule Sets | 0.5.0 | 0.5.0 |
VAR.etp VAR Modelling: Estimation, Testing, and Prediction | 1.0 | 1.0 |
vardiag Variogram Diagnostics | 0.2-1 | 0.2-1 |
vardpoor Variance Estimation for Sample Surveys by the Ultimate Cluster Method | 0.20.1 | 0.20.1 |
variables Variable Descriptions | 1.1-1 | 1.1-1 |
VarianceGamma The Variance Gamma Distribution | 0.4-0 | 0.4-0 |
VariantAnnotation | 1.42.0 | 1.42.0 |
varImp RF Variable Importance for Arbitrary Measures | 0.4 | 0.4 |
vars VAR Modelling | 1.5-6 | 1.5-6 |
VarSelLCM Variable Selection for Model-Based Clustering of Mixed-Type Data Set with Missing Values | 2.1.3.1 | 2.1.3.1 |
varSelRF Variable Selection using Random Forests | 0.7-8 | 0.7-8 |
VARshrink Shrinkage Estimation Methods for Vector Autoregressive Models | 0.3.1 | 0.3.1 |
VARsignR Sign Restrictions, Bayesian, Vector Autoregression Models | 0.1.3 | 0.1.3 |
VarSwapPrice Pricing a variance swap on an equity index | 1.0 | 1.0 |
VCA Variance Component Analysis | 1.4.5 | 1.4.5 |
vcd Visualizing Categorical Data | 1.4-9 | 1.4-9 |
vcdExtra 'vcd' Extensions and Additions | 0.8-2 | 0.8-2 |
vctrs Vector Helpers | 0.6.1 | 0.6.1 |
vdiffr Visual Regression Testing and Graphical Diffing | 1.0.4 | 1.0.4 |
vec2dtransf 2D Cartesian Coordinate Transformation | 1.1.2 | 1.1.2 |
vegan Community Ecology Package | 2.6-4 | 2.6-4 |
vegetarian Jost Diversity Measures for Community Data | 1.2 | 1.2 |
VennDiagram Generate High-Resolution Venn and Euler Plots | 1.7.3 | 1.7.3 |
venneuler Venn and Euler Diagrams | 1.1-3 | 1.1-3 |
versions Query and Install Specific Versions of Packages on CRAN | 0.3 | 0.3 |
VeryLargeIntegers Store and Operate with Arbitrarily Large Integers | 0.1.9 | 0.1.9 |
VGAM Vector Generalized Linear and Additive Models | 1.1-7 | 1.1-7 |
VIM Visualization and Imputation of Missing Values | 6.2.2 | 6.2.2 |
vimp Perform Inference on Algorithm-Agnostic Variable Importance | 2.2.5 | 2.2.5 |
VineCopula Statistical Inference of Vine Copulas | 2.4.5 | 2.4.5 |
vines Multivariate Dependence Modeling with Vines | 1.1.5 | 1.1.5 |
vioplot Violin Plot | 0.4.0 | 0.4.0 |
vip Variable Importance Plots | 0.3.2 | 0.3.2 |
vipor Plot Categorical Data Using Quasirandom Noise and Density Estimates | 0.4.5 | 0.4.5 |
viridis Colorblind-Friendly Color Maps for R | 0.6.2 | 0.6.2 |
viridisLite Colorblind-Friendly Color Maps (Lite Version) | 0.4.1 | 0.4.1 |
visdat Preliminary Visualisation of Data | 0.6.0 | 0.6.0 |
visNetwork Network Visualization using 'vis.js' Library | 2.1.2 | 2.1.2 |
visreg Visualization of Regression Models | 2.7.0 | 2.7.0 |
vistributions Visualize Probability Distributions | 0.1.2 | 0.1.2 |
visualize Graph Probability Distributions with User Supplied Parameters and Statistics | 4.4.0 | 4.4.0 |
vitality Fitting Routines for the Vitality Family of Mortality Models | 1.3 | 1.3 |
vkR Access to VK API via R | 0.2 | 0.2 |
vpc Create Visual Predictive Checks | 1.2.2 | 1.2.2 |
vroom Read and Write Rectangular Text Data Quickly | 1.6.1 | 1.6.1 |
vrtest Variance Ratio Tests and Other Tests for Martingale Difference Hypothesis | 1.1 | 1.1 |
vsgoftest Goodness-of-Fit Tests Based on Kullback-Leibler Divergence | 1.0-1 | 1.0-1 |
vtable Variable Table for Variable Documentation | 1.3.3 | 1.3.3 |
VTrack A Collection of Tools for the Analysis of Remote Acoustic Telemetry Data | 1.21 | 1.21 |
W3CMarkupValidator R Interface to W3C Markup Validation Services | 0.1-7 | 0.1-7 |
wahc Autocorrelation and Heteroskedasticity Correction in Fixed Effect Panel Data Model | 1.0 | 1.0 |
waiter Loading Screen for 'Shiny' | 0.2.5 | 0.2.5 |
waldo Find Differences Between R Objects | 0.4.0 | 0.4.0 |
walrus Robust Statistical Methods | 1.0.4 | 1.0.4 |
warp Group Dates | 0.2.0 | 0.2.0 |
warpMix Mixed Effects Modeling with Warping for Functional Data Using B-Spline | 0.1.0 | 0.1.0 |
washdata Urban Water and Sanitation Survey Dataset | 0.1.3 | 0.1.3 |
wasim Visualisation and analysis of output files of the hydrological model WASIM | 1.1.2 | 1.1.2 |
water Actual Evapotranspiration with Energy Balance Models | 0.8 | 0.8 |
waterData Retrieval, Analysis, and Anomaly Calculation of Daily Hydrologic Time Series Data | 1.0.8 | 1.0.8 |
Watersheds Spatial Watershed Aggregation and Spatial Drainage Network Analysis | 1.1 | 1.1 |
WaveletComp Computational Wavelet Analysis | 1.1 | 1.1 |
wavelets Functions for Computing Wavelet Filters, Wavelet Transforms and Multiresolution Analyses | 0.3-0.2 | 0.3-0.2 |
WaverR Data Estimation using Weighted Averages of Multiple Regressions | 1.0 | 1.0 |
waveslim Basic Wavelet Routines for One-, Two-, and Three-Dimensional Signal Processing | 1.8.4 | 1.8.4 |
wavethresh Wavelets Statistics and Transforms | 4.7.2 | 4.7.2 |
wavScalogram Wavelet Scalogram Tools for Time Series Analysis | 1.1.2 | 1.1.2 |
wbstats Programmatic Access to Data and Statistics from the World Bank API | 1.0.4 | 1.0.4 |
wbsts Multiple Change-Point Detection for Nonstationary Time Series | 2.1 | 2.1 |
wCorr Weighted Correlations | 1.9.6 | 1.9.6 |
WDI World Development Indicators and Other World Bank Data | 2.7.6 | 2.7.6 |
wdman 'Webdriver'/'Selenium' Binary Manager | 0.2.6 | 0.2.6 |
weathercan Download Weather Data from Environment and Climate Change Canada | 0.6.1 | 0.6.1 |
webchem Chemical Information from the Web | 1.2.0 | 1.2.0 |
webdriver 'WebDriver' Client for 'PhantomJS' | 1.0.6 | 1.0.6 |
WebGestaltR Gene Set Analysis Toolkit WebGestaltR | 0.4.4 | 0.4.4 |
webp A New Format for Lossless and Lossy Image Compression | 1.1.0 | 1.1.0 |
webreadr Tools for Reading Formatted Access Log Files | 0.4.0 | 0.4.0 |
webshot Take Screenshots of Web Pages | 0.5.4 | 0.5.4 |
websocket 'WebSocket' Client Library | 1.4.1 | 1.4.1 |
webutils Utility Functions for Developing Web Applications | 1.1 | 1.1 |
wedge The Exterior Calculus | 1.0-3 | 1.0-3 |
WeightedPortTest Weighted Portmanteau Tests for Time Series Goodness-of-fit | 1.0 | 1.0 |
WeightIt Weighting for Covariate Balance in Observational Studies | 0.13.1 | 0.13.1 |
weightr Estimating Weight-Function Models for Publication Bias | 2.0.2 | 2.0.2 |
weights Weighting and Weighted Statistics | 1.0.4 | 1.0.4 |
wellknown Convert Between 'WKT' and 'GeoJSON' | 0.7.4 | 0.7.4 |
WeMix Weighted Mixed-Effects Models Using Multilevel Pseudo Maximum Likelihood Estimation | 3.2.4 | 3.2.4 |
wesanderson A Wes Anderson Palette Generator | 0.3.6 | 0.3.6 |
wevid Quantifying Performance of a Binary Classifier Through Weight of Evidence | 0.6.2 | 0.6.2 |
wgaim Whole Genome Average Interval Mapping for QTL Detection and Estimation using ASReml-R | 2.0-1 | 2.0-1 |
WGCNA Weighted Correlation Network Analysis | 1.71 | 1.71 |
whisker {{mustache}} for R, Logicless Templating | 0.4 | 0.4 |
whoami Username, Full Name, Email Address, 'GitHub' Username of the Current User | 1.3.0 | 1.3.0 |
widgetframe 'Htmlwidgets' in Responsive 'iframes' | 0.3.1 | 0.3.1 |
WikidataQueryServiceR API Client Library for 'Wikidata Query Service' | 1.0.0 | 1.0.0 |
WikidataR Read-Write API Client Library for Wikidata | 2.3.3 | 2.3.3 |
wikipediatrend Public Subject Attention via Wikipedia Page View Statistics | 2.1.6 | 2.1.6 |
WikipediR A MediaWiki API Wrapper | 1.5.0 | 1.5.0 |
wikitaxa Taxonomic Information from 'Wikipedia' | 0.4.0 | 0.4.0 |
WilcoxCV Wilcoxon-based variable selection in cross-validation | 1.0-2 | 1.0-2 |
wildlifeDI Calculate Indices of Dynamic Interaction for Wildlife Tracking Data | 0.5.0 | 0.5.0 |
windex Analysing Convergent Evolution using the Wheatsheaf Index | 2.0.4.1 | 2.0.4.1 |
withr Run Code 'With' Temporarily Modified Global State | 2.5.0 | 2.5.0 |
wk Lightweight Well-Known Geometry Parsing | 0.6.0 | 0.6.0 |
wkb Convert Between Spatial Objects and Well-Known Binary Geometry | 0.4-0 | 0.4-0 |
wktmo Converting Weekly Data to Monthly Data | 1.0.5 | 1.0.5 |
wmtsa Wavelet Methods for Time Series Analysis | 2.0-3 | 2.0-3 |
wNNSel Weighted Nearest Neighbor Imputation of Missing Values using Selected Variables | 0.1 | 0.1 |
womblR Spatiotemporal Boundary Detection Model for Areal Unit Data | 1.0.4 | 1.0.4 |
wooldridge 115 Data Sets from "Introductory Econometrics: A Modern Approach, 7e" by Jeffrey M. Wooldridge | 1.4-2 | 1.4-2 |
wordcloud Word Clouds | 2.6 | 2.6 |
wordcloud2 Create Word Cloud by 'htmlwidget' | 0.2.1 | 0.2.1 |
wordnet WordNet Interface | 0.1-16 | 0.1-16 |
workflowr A Framework for Reproducible and Collaborative Data Science | 1.7.0 | 1.7.0 |
workflows Modeling Workflows | 0.2.6 | 0.2.6 |
workflowsets Create a Collection of 'tidymodels' Workflows | 0.2.1 | 0.2.1 |
worldmet Import Surface Meteorological Data from NOAA Integrated Surface Database (ISD) | 0.9.7 | 0.9.7 |
worrms World Register of Marine Species (WoRMS) Client | 0.4.2 | 0.4.2 |
wql Exploring Water Quality Monitoring Data | 1.0.0 | 1.0.0 |
wrangle A Systematic Data Wrangling Idiom | 0.5.10 | 0.5.10 |
Wrapped Computes Pdf, Cdf, Quantile, Random Numbers and Provides Estimation for any Univariate Wrapped Distributions | 2.0 | 2.0 |
wrapr Wrap R Tools for Debugging and Parametric Programming | 2.0.9 | 2.0.9 |
WrightMap IRT Item-Person Map with 'ConQuest' Integration | 1.3 | 1.3 |
writexl Export Data Frames to Excel 'xlsx' Format | 1.4.2 | 1.4.2 |
WriteXLS Cross-Platform Perl Based R Function to Create Excel 2003 (XLS) and Excel 2007 (XLSX) Files | 6.4.0 | 6.4.0 |
WRS2 A Collection of Robust Statistical Methods | 1.1-4 | 1.1-4 |
WRSS Water Resources System Simulator | 3.1 | 3.1 |
wrswoR Weighted Random Sampling without Replacement | 1.1.1 | 1.1.1 |
WRTDStidal Weighted Regression for Water Quality Evaluation in Tidal Waters | 1.1.2 | 1.1.2 |
wsrf Weighted Subspace Random Forest for Classification | 1.7.27 | 1.7.27 |
wTO Computing Weighted Topological Overlaps (wTO) & Consensus wTO Network | 1.6.3 | 1.6.3 |
WufooR R Wrapper for the 'Wufoo.com' - The Form Building Service | 1.0.1 | 1.0.1 |
wwntests Hypothesis Tests for Functional Time Series | 1.0.1 | 1.0.1 |
x12 Interface to 'X12-ARIMA'/'X13-ARIMA-SEATS' and Structure for Batch Processing of Seasonal Adjustment | 1.10.2 | 1.10.2 |
x13binary Provide the 'x13ashtml' Seasonal Adjustment Binary | 1.1.57-3 | 1.1.57-3 |
xaringan Presentation Ninja | 0.24 | 0.24 |
XBRL Extraction of Business Financial Information from 'XBRL' Documents | 0.99.19.1 | 0.99.19.1 |
xfun Supporting Functions for Packages Maintained by 'Yihui Xie' | 0.37 | 0.37 |
xgboost Extreme Gradient Boosting | 1.7.3.1 | 1.7.3.1 |
xgobi Interface to the XGobi and XGvis programs for graphical data analysis | 1.2-15 | 1.2-15 |
xmeta A Toolbox for Multivariate Meta-Analysis | 1.3-0 | 1.3-0 |
XML Tools for Parsing and Generating XML Within R and S-Plus | 3.99-0.14 | 3.99-0.14 |
xml2 Parse XML | 1.3.3 | 1.3.3 |
XML2R EasieR XML data collection | 0.0.6 | 0.0.6 |
xmlparsedata Parse Data of 'R' Code as an 'XML' Tree | 1.0.5 | 1.0.5 |
xmlrpc2 Implementation of the Remote Procedure Call Protocol ('XML-RPC') | 1.1 | 1.1 |
XMRF Markov Random Fields for High-Throughput Genetics Data | 1.0 | 1.0 |
xopen Open System Files, 'URLs', Anything | 1.0.0 | 1.0.0 |
xplain Providing Interactive Interpretations and Explanations of Statistical Results | 0.2.2 | 0.2.2 |
xpose Diagnostics for Pharmacometric Models | 0.4.15 | 0.4.15 |
XR A Structure for Interfaces from R | 0.7.2 | 0.7.2 |
XRJulia Structured Interface to Julia | 0.9.0 | 0.9.0 |
XRPython Structured Interface to 'Python' | 0.8 | 0.8 |
xslt Extensible Style-Sheet Language Transformations | 1.4.4 | 1.4.4 |
xtable Export Tables to LaTeX or HTML | 1.8-4 | 1.8-4 |
xts eXtensible Time Series | 0.13.0 | 0.13.0 |
XVector | 0.36.0 | 0.36.0 |
xxIRT Item Response Theory and Computer-Based Testing in R | 2.1.2 | 2.1.2 |
yaImpute Nearest Neighbor Observation Imputation and Evaluation Tools | 1.0-33 | 1.0-33 |
YaleToolkit Data Exploration Tools from Yale University | 4.2.2 | 4.2.2 |
yaml Methods to Convert R Data to YAML and Back | 2.3.7 | 2.3.7 |
yardstick Tidy Characterizations of Model Performance | 0.0.9 | 0.0.9 |
ycinterextra Yield curve or zero-coupon prices interpolation and<U+000a>extrapolation | 0.1 | 0.1 |
yesno Ask Yes-No Questions | 0.1.2 | 0.1.2 |
yhatr R Binder for the Yhat API | 0.15.1 | 0.15.1 |
YieldCurve Modelling and Estimation of the Yield Curve | 4.1 | 4.1 |
yuima The YUIMA Project Package for SDEs | 1.15.22 | 1.15.22 |
yulab.utils Supporting Functions for Packages Maintained by 'YuLab-SMU' | 0.0.5 | 0.0.5 |
yummlyr R Bindings for Yummly API | 0.1.1 | 0.1.1 |
zeallot Multiple, Unpacking, and Destructuring Assignment | 0.1.0 | 0.1.0 |
zen4R Interface to 'Zenodo' REST API | 0.5-3 | 0.5-3 |
zendeskR Zendesk API Wrapper | 0.4 | 0.4 |
zic Bayesian Inference for Zero-Inflated Count Models | 0.9.1 | 0.9.1 |
ZillowR R Interface to Zillow Real Estate and Mortgage Data API | 1.0.0 | 1.0.0 |
ZIM Zero-Inflated Models (ZIM) for Count Time Series with Excess Zeros | 1.1.0 | 1.1.0 |
zip Cross-Platform 'zip' Compression | 2.2.2 | 2.2.2 |
zipfextR Zipf Extended Distributions | 1.0.2 | 1.0.2 |
zipfR Statistical Models for Word Frequency Distributions | 0.6-70 | 0.6-70 |
zlibbioc | 1.42.0 | 1.42.0 |
zoo S3 Infrastructure for Regular and Irregular Time Series (Z's Ordered Observations) | 1.8-11 | 1.8-11 |
zoom A Spatial Data Visualization Tool | 2.0.6 | 2.0.6 |
ZRA Dynamic Plots for Time Series Forecasting | 0.2 | 0.2 |
Zseq Integer Sequence Generator | 0.2.1 | 0.2.1 |
ztable Zebra-Striped Tables in LaTeX and HTML Formats | 0.2.3 | 0.2.3 |
zTree Functions to Import Data from 'z-Tree' into R | 1.0.7 | 1.0.7 |
zyp Zhang + Yue-Pilon Trends Package | 0.11-1 | 0.11-1 |
This information was collected at 20230331-0950.