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-sage
or 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 |