Installed R Statistical Software Packages (Ubuntu 22.04)
This table lists all R pre-installed packages that are immediately available in every CoCalc project running on the default "Ubuntu 22.04" 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 4.4.1 (2024-06-14) -- "Race for Your Life" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu 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 4.4.1 (2024-06-14) -- "Race for Your Life" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu 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 5292 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 |
abcrf Approximate Bayesian Computation via Random Forests | 1.9 | 1.9 |
abess Fast Best Subset Selection | 0.4.8 | 0.4.8 |
abglasso Adaptive Bayesian Graphical Lasso | 0.1.1 | 0.1.1 |
abind Combine Multidimensional Arrays | 1.4-5 | 1.4-5 |
abtest Bayesian A/B Testing | 1.0.1 | 1.0.1 |
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 |
acebayes Optimal Bayesian Experimental Design using the ACE Algorithm | 1.10 | 1.10 |
acepack ACE and AVAS for Selecting Multiple Regression Transformations | 1.4.2 | 1.4.2 |
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 |
activityCounts Generate ActiLife Counts | 0.1.2 | 0.1.2 |
actuar Actuarial Functions and Heavy Tailed Distributions | 3.3-4 | 3.3-4 |
ada The R Package Ada for Stochastic Boosting | 2.0-5 | 2.0-5 |
adabag Applies Multiclass AdaBoost.M1, SAMME and Bagging | 5.0 | 5.0 |
adagio Discrete and Global Optimization Routines | 0.9.2 | 0.9.2 |
adaptivetau Tau-Leaping Stochastic Simulation | 2.3 | 2.3 |
adaptMCMC Implementation of a Generic Adaptive Monte Carlo Markov Chain Sampler | 1.5 | 1.5 |
adaptMT Adaptive P-Value Thresholding for Multiple Hypothesis Testing with Side Information | 1.0.0 | 1.0.0 |
adaptTest Adaptive Two-Stage Tests | 1.2 | 1.2 |
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 | 1.0-21 | 1.0-21 |
adehabitatHR Home Range Estimation | 0.4.21 | 0.4.21 |
adehabitatHS Analysis of Habitat Selection by Animals | 0.3.17 | 0.3.17 |
adehabitatLT Analysis of Animal Movements | 0.3.27 | 0.3.27 |
adehabitatMA Tools to Deal with Raster Maps | 0.3.16 | 0.3.16 |
adephylo Exploratory Analyses for the Phylogenetic Comparative Method | 1.1-16 | 1.1-16 |
AdequacyModel Adequacy of Probabilistic Models and General Purpose Optimization | 2.0.0 | 2.0.0 |
adespatial Multivariate Multiscale Spatial Analysis | 0.3-16 | 0.3-16 |
ADGofTest Anderson-Darling GoF test | 0.3 | 0.3 |
adimpro Adaptive Smoothing of Digital Images | 0.9.6 | 0.9.6 |
adiv Analysis of Diversity | 2.1.2 | 2.1.2 |
admisc Adrian Dusa's Miscellaneous | 0.34 | 0.34 |
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 | 1.5-10 | 1.5-10 |
AdvancedBasketballStats Advanced Basketball Statistics | 1.0.1 | 1.0.1 |
AER Applied Econometrics with R | 1.2-10 | 1.2-10 |
AeRobiology A Computational Tool for Aerobiological Data | 2.0.1 | 2.0.1 |
afex Analysis of Factorial Experiments | 1.3-0 | 1.3-0 |
affxparser | 1.70.0 | 1.70.0 |
affy | 1.80.0 | 1.80.0 |
affydata | 1.46.0 | 1.46.0 |
affyio | 1.72.0 | 1.72.0 |
affyPLM | 1.74.1 | 1.74.1 |
aftgee Accelerated Failure Time Model with Generalized Estimating Equations | 1.2.0 | 1.2.0 |
aggregation p-Value Aggregation Methods | 1.0.1 | 1.0.1 |
agricolae Statistical Procedures for Agricultural Research | 1.3-5 | 1.3-5 |
agridat Agricultural Datasets | 1.22 | 1.22 |
AGSDest Estimation in Adaptive Group Sequential Trials | 2.3.4 | 2.3.4 |
ahaz Regularization for Semiparametric Additive Hazards Regression | 1.15 | 1.15 |
AIPW Augmented Inverse Probability Weighting | 0.6.3.2 | 0.6.3.2 |
airGR Suite of GR Hydrological Models for Precipitation-Runoff Modelling | 1.7.6 | 1.7.6 |
airGRdatassim Ensemble-Based Data Assimilation with GR Hydrological Models | 0.1.3 | 0.1.3 |
airGRteaching Teaching Hydrological Modelling with the GR Rainfall-Runoff Models ('Shiny' Interface Included) | 0.3.2 | 0.3.2 |
airports Data on Airports | 0.1.0 | 0.1.0 |
airr AIRR Data Representation Reference Library | 1.5.0 | 1.5.0 |
ajv Another JSON Schema Validator | 1.0.0 | 1.0.0 |
akima Interpolation of Irregularly and Regularly Spaced Data | 0.6-3.4 | 0.6-3.4 |
alabama Constrained Nonlinear Optimization | 2023.1.0 | 2023.1.0 |
ald The Asymmetric Laplace Distribution | 1.3.1 | 1.3.1 |
AlgDesign Algorithmic Experimental Design | 1.2.1 | 1.2.1 |
alleHap Allele Imputation and Haplotype Reconstruction from Pedigree Databases | 0.9.9 | 0.9.9 |
allestimates Effect Estimates from All Models | 0.2.3 | 0.2.3 |
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 | 2.5 | 2.5 |
alphavantager Lightweight Interface to the Alpha Vantage API | 0.1.3 | 0.1.3 |
altmeta Alternative Meta-Analysis Methods | 4.1 | 4.1 |
ALTopt Optimal Experimental Designs for Accelerated Life Testing | 0.1.2 | 0.1.2 |
amanida Meta-Analysis for Non-Integral Data | 0.2.3 | 0.2.3 |
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 |
ammiBayes Bayesian Ammi Model for Continuous Data | 1.0-1 | 1.0-1 |
AMORE Artificial Neural Network Training and Simulating | 0.2-16 | 0.2-16 |
amt Animal Movement Tools | 0.2.1.0 | 0.2.1.0 |
AnaCoDa Analysis of Codon Data under Stationarity using a Bayesian Framework | 0.1.4.4 | 0.1.4.4 |
anacor Simple and Canonical Correspondence Analysis | 1.1-4 | 1.1-4 |
analogsea Interface to 'DigitalOcean' | 1.0.7.2 | 1.0.7.2 |
analogue Analogue and Weighted Averaging Methods for Palaeoecology | 0.17-6 | 0.17-6 |
Andromeda Asynchronous Disk-Based Representation of Massive Data | 0.6.5 | 0.6.5 |
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 | 0.10.1 | 0.10.1 |
anMC Compute High Dimensional Orthant Probabilities | 0.2.5 | 0.2.5 |
annotate | 1.80.0 | 1.80.0 |
AnnotationDbi | 1.64.1 | 1.64.1 |
AnnotationFilter | 1.22.0 | 1.22.0 |
AnnotationHub | 3.10.0 | 3.10.0 |
anomaly Detecting Anomalies in Data | 4.0.2 | 4.0.2 |
Anthropometry Statistical Methods for Anthropometric Data | 1.19 | 1.19 |
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 | 1.3.3 | 1.3.3 |
aoos Another Object Orientation System | 0.5.0 | 0.5.0 |
AovBay Classic, Nonparametric and Bayesian One-Way Analysis of Variance Panel | 0.1.0 | 0.1.0 |
apcluster Affinity Propagation Clustering | 1.4.11 | 1.4.11 |
ape Analyses of Phylogenetics and Evolution | 5.7-1 | 5.7-1 |
apex Phylogenetic Methods for Multiple Gene Data | 1.0.4 | 1.0.4 |
APFr Multiple Testing Approach using Average Power Function (APF) and Bayes FDR Robust Estimation | 1.0.2 | 1.0.2 |
aplore3 Datasets from Hosmer, Lemeshow and Sturdivant, "Applied Logistic Regression" (3rd Ed., 2013) | 0.9 | 0.9 |
aplot Decorate a 'ggplot' with Associated Information | 0.2.2 | 0.2.2 |
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 | 0.3.1 | 0.3.1 |
AppliedPredictiveModeling Functions and Data Sets for 'Applied Predictive Modeling' | 1.1-7 | 1.1-7 |
approximator Bayesian Prediction of Complex Computer Codes | 1.2-8 | 1.2-8 |
approxmatch Approximately Optimal Fine Balance Matching with Multiple Groups | 2.0 | 2.0 |
aprof Amdahl's Profiler, Directed Optimization Made Easy | 0.4.1 | 0.4.1 |
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 |
aqp Algorithms for Quantitative Pedology | 2.0.2 | 2.0.2 |
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 | 3.0.1 | 3.0.1 |
ArchaeoChron Bayesian Modeling of Archaeological Chronologies | 0.1 | 0.1 |
ArchaeoPhases Post-Processing of the Markov Chain Simulated by 'ChronoModel', 'Oxcal' or 'BCal' | 1.8 | 1.8 |
archetypes Archetypal Analysis | 2.2-0.1 | 2.2-0.1 |
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 | 0.1.8 | 0.1.8 |
argo Accurate Estimation of Influenza Epidemics using Google Search Data | 3.0.2 | 3.0.2 |
argosfilter Argos Locations Filter | 0.70 | 0.70 |
argparse Command Line Optional and Positional Argument Parser | 2.1.3 | 2.1.3 |
argparser Command-Line Argument Parser | 0.7.1 | 0.7.1 |
aricode Efficient Computations of Standard Clustering Comparison Measures | 1.0.3 | 1.0.3 |
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 |
arrow Integration to 'Apache' 'Arrow' | 10.0.1 | 10.0.1 |
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 | 1.7-7 | 1.7-7 |
arulesCBA Classification Based on Association Rules | 1.2.5 | 1.2.5 |
arulesSequences Mining Frequent Sequences | 0.2-30 | 0.2-30 |
aRxiv Interface to the arXiv API | 0.8 | 0.8 |
asaur Data Sets for "Applied Survival Analysis Using R"" | 0.50 | 0.50 |
asbio A Collection of Statistical Tools for Biologists | 1.9-7 | 1.9-7 |
ascii Export R Objects to Several Markup Languages | 2.4 | 2.4 |
asd Simulations for Adaptive Seamless Designs | 2.2 | 2.2 |
ash David Scott's ASH Routines | 1.0-15 | 1.0-15 |
ashr Methods for Adaptive Shrinkage, using Empirical Bayes | 2.2-63 | 2.2-63 |
AsioHeaders 'Asio' C++ Header Files | 1.22.1-2 | 1.22.1-2 |
askpass Safe Password Entry for R, Git, and SSH | 1.2.0 | 1.2.0 |
ASPBay Bayesian Inference on Causal Genetic Variants using Affected Sib-Pairs Data | 1.2 | 1.2 |
aspect A General Framework for Multivariate Analysis with Optimal Scaling | 1.0-6 | 1.0-6 |
ASSA Applied Singular Spectrum Analysis (ASSA) | 2.0 | 2.0 |
assemblerr Assembly of Pharmacometric Models | 0.1.1 | 0.1.1 |
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 | 0.0-4 | 0.0-4 |
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 |
AssetCorr Estimating Asset Correlations from Default Data | 1.0.4 | 1.0.4 |
aster Aster Models | 1.1-3 | 1.1-3 |
aster2 Aster Models | 0.3 | 0.3 |
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 | 2.1 | 2.1 |
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 |
ata Automated Test Assembly | 1.1.1 | 1.1.1 |
ath1121501.db | 3.13.0 | 3.13.0 |
ath1121501cdf | 2.18.0 | 2.18.0 |
atmcmc Automatically Tuned Markov Chain Monte Carlo | 1.0 | 1.0 |
ATmet Advanced Tools for Metrology | 1.2.1 | 1.2.1 |
aTSA Alternative Time Series Analysis | 3.1.2 | 3.1.2 |
attempt Tools for Defensive Programming | 0.3.1 | 0.3.1 |
attention Self-Attention Algorithm | 0.4.0 | 0.4.0 |
autoFRK Automatic Fixed Rank Kriging | 1.4.3 | 1.4.3 |
autohd High Dimensional Bayesian Survival Mediation Analysis | 0.1.0 | 0.1.0 |
autoimage Multiple Heat Maps for Projected Coordinates | 2.2.3 | 2.2.3 |
automap Automatic Interpolation Package | 1.1-9 | 1.1-9 |
autostsm Automatic Structural Time Series Models | 3.1.2 | 3.1.2 |
av Working with Audio and Video in R | 0.8.3 | 0.8.3 |
aweek Convert Dates to Arbitrary Week Definitions | 1.0.3 | 1.0.3 |
aws Adaptive Weights Smoothing | 2.5-3 | 2.5-3 |
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 |
AzureCognitive Interface to Azure Cognitive Services | 1.0.1 | 1.0.1 |
AzureContainers Interface to 'Container Instances', 'Docker Registry' and 'Kubernetes' in 'Azure' | 1.3.2 | 1.3.2 |
AzureCosmosR Interface to the 'Azure Cosmos DB' 'NoSQL' Database Service | 1.0.0 | 1.0.0 |
AzureGraph Simple Interface to 'Microsoft Graph' | 1.3.4 | 1.3.4 |
AzureKusto Interface to 'Kusto'/'Azure Data Explorer' | 1.1.3 | 1.1.3 |
AzureQstor Interface to 'Azure Queue Storage' | 1.0.1 | 1.0.1 |
AzureRMR Interface to 'Azure Resource Manager' | 2.4.4 | 2.4.4 |
AzureStor Storage Management in 'Azure' | 3.7.0 | 3.7.0 |
AzureTableStor Interface to the Table Storage Service in 'Azure' | 1.0.0 | 1.0.0 |
AzureVision Interface to Azure Computer Vision Services | 1.0.2 | 1.0.2 |
AzureVM Virtual Machines in 'Azure' | 2.2.2 | 2.2.2 |
babar Bayesian Bacterial Growth Curve Analysis in R | 1.0 | 1.0 |
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) | 2.1-0 | 2.1-0 |
BACCT Bayesian Augmented Control for Clinical Trials | 1.0 | 1.0 |
backbone Extracts the Backbone from Graphs | 2.1.3 | 2.1.3 |
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 |
bacondecomp Goodman-Bacon Decomposition | 0.1.1 | 0.1.1 |
baggr Bayesian Aggregate Treatment Effects | 0.7.6 | 0.7.6 |
bain Bayes Factors for Informative Hypotheses | 0.2.10 | 0.2.10 |
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 |
bama High Dimensional Bayesian Mediation Analysis | 1.3.0 | 1.3.0 |
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) | 1.2-2 | 1.2-2 |
BAMMtools Analysis and Visualization of Macroevolutionary Dynamics on Phylogenetic Trees | 2.1.11 | 2.1.11 |
bang Bayesian Analysis, No Gibbs | 1.0.3 | 1.0.3 |
BANOVA Hierarchical Bayesian ANOVA Models | 1.2.1 | 1.2.1 |
BaPreStoPro Bayesian Prediction of Stochastic Processes | 0.1 | 0.1 |
BART Bayesian Additive Regression Trees | 2.9.6 | 2.9.6 |
bartBMA Bayesian Additive Regression Trees using Bayesian Model Averaging | 1.0 | 1.0 |
bartCause Causal Inference using Bayesian Additive Regression Trees | 1.0-6 | 1.0-6 |
bartMachine Bayesian Additive Regression Trees | 1.3.4.1 | 1.3.4.1 |
bartMachineJARs bartMachine JARs | 1.2.1 | 1.2.1 |
BAS Bayesian Variable Selection and Model Averaging using Bayesian Adaptive Sampling | 1.7.1 | 1.7.1 |
basad Bayesian Variable Selection with Shrinking and Diffusing Priors | 0.3.0 | 0.3.0 |
base | 4.4.1 | 4.4.1 |
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 |
baseballDBR Sabermetrics and Advanced Baseball Statistics | 0.1.2 | 0.1.2 |
baseballr Acquiring and Analyzing Baseball Data | 1.6.0 | 1.6.0 |
basefun Infrastructure for Computing with Basis Functions | 1.1-4 | 1.1-4 |
baseline Baseline Correction of Spectra | 1.3-5 | 1.3-5 |
basicMCMCplots Trace Plots, Density Plots and Chain Comparisons for MCMC Samples | 0.2.7 | 0.2.7 |
BaSkePro Bayesian Model to Archaeological Faunal Skeletal Profiles | 1.1.1 | 1.1.1 |
BasketballAnalyzeR Analysis and Visualization of Basketball Data | 0.5.0 | 0.5.0 |
BASS Bayesian Adaptive Spline Surfaces | 1.3.1 | 1.3.1 |
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 | 0.9.17 | 0.9.17 |
BAwiR Analysis of Basketball Data | 1.3.1 | 1.3.1 |
baycn Bayesian Inference for Causal Networks | 1.2.0 | 1.2.0 |
bayefdr Bayesian Estimation and Optimisation of Expected False Discovery Rate | 0.2.1 | 0.2.1 |
bayes4psy User Friendly Bayesian Data Analysis for Psychology | 1.2.12 | 1.2.12 |
bayesAB Fast Bayesian Methods for AB Testing | 1.1.3 | 1.1.3 |
bayesammi Bayesian Estimation of the Additive Main Effects and Multiplicative Interaction Model | 0.1.0 | 0.1.0 |
bayesanova Bayesian Inference in the Analysis of Variance via Markov Chain Monte Carlo in Gaussian Mixture Models | 1.5 | 1.5 |
BayesARIMAX Bayesian Estimation of ARIMAX Model | 0.1.1 | 0.1.1 |
BayesBinMix Bayesian Estimation of Mixtures of Multivariate Bernoulli Distributions | 1.4.1 | 1.4.1 |
bayesbio Miscellaneous Functions for Bioinformatics and Bayesian Statistics | 1.0.0 | 1.0.0 |
bayesboot An Implementation of Rubin's (1981) Bayesian Bootstrap | 0.2.2 | 0.2.2 |
BayesBP Bayesian Estimation using Bernstein Polynomial Fits Rate Matrix | 1.1 | 1.1 |
bayesbr Beta Regression on a Bayesian Model | 0.0.1.0 | 0.0.1.0 |
BayesCACE Bayesian Model for CACE Analysis | 1.2.3 | 1.2.3 |
BayesCombo Bayesian Evidence Combination | 1.0 | 1.0 |
BayesComm Bayesian Community Ecology Analysis | 0.1-2 | 0.1-2 |
bayescopulareg Bayesian Copula Regression | 0.1.3 | 0.1.3 |
bayescount Power Calculations and Bayesian Analysis of Count Distributions and FECRT Data using MCMC | 0.9.99-9 | 0.9.99-9 |
BayesCR Bayesian Analysis of Censored Regression Models Under Scale Mixture of Skew Normal Distributions | 2.1 | 2.1 |
bayesCT Simulation and Analysis of Adaptive Bayesian Clinical Trials | 0.99.3 | 0.99.3 |
BayesCTDesign Two Arm Bayesian Clinical Trial Design with and Without Historical Control Data | 0.6.1 | 0.6.1 |
BayesDA Functions and Datasets for the book "Bayesian Data Analysis" | 2012.04-1 | 2012.04-1 |
bayesDccGarch Methods and Tools for Bayesian Dynamic Conditional Correlation GARCH(1,1) Model | 3.0.4 | 3.0.4 |
bayesdfa Bayesian Dynamic Factor Analysis (DFA) with 'Stan' | 1.3.2 | 1.3.2 |
bayesdistreg Bayesian Distribution Regression | 0.1.0 | 0.1.0 |
bayesDP Implementation of the Bayesian Discount Prior Approach for Clinical Trials | 1.3.6 | 1.3.6 |
BayesFactor Computation of Bayes Factors for Common Designs | 0.9.12-4.7 | 0.9.12-4.7 |
BayesFM Bayesian Inference for Factor Modeling | 0.1.5 | 0.1.5 |
bayesforecast Bayesian Time Series Modeling with Stan | 1.0.1 | 1.0.1 |
bayesGAM Fit Multivariate Response Generalized Additive Models using Hamiltonian Monte Carlo | 0.0.2 | 0.0.2 |
bayesGARCH Bayesian Estimation of the GARCH(1,1) Model with Student-t Innovations | 2.1.10 | 2.1.10 |
BayesGESM Bayesian Analysis of Generalized Elliptical Semi-Parametric Models and Flexible Measurement Error Models | 1.4 | 1.4 |
BayesGOF Bayesian Modeling via Frequentist Goodness-of-Fit | 5.2 | 5.2 |
BayesGPfit Fast Bayesian Gaussian Process Regression Fitting | 1.1.0 | 1.1.0 |
BayesGWQS Bayesian Grouped Weighted Quantile Sum Regression | 0.1.1 | 0.1.1 |
bayesian Bindings for Bayesian TidyModels | 0.0.9 | 0.0.9 |
BayesianAnimalTracker Bayesian Melding of GPS and DR Path for Animal Tracking | 1.2 | 1.2 |
bayesianETAS Bayesian Estimation of the ETAS Model for Earthquake Occurrences | 1.0.3 | 1.0.3 |
BayesianFROC FROC Analysis by Bayesian Approaches | 1.0.0 | 1.0.0 |
Bayesiangammareg Bayesian Gamma Regression: Joint Mean and Shape Modeling | 0.1.0 | 0.1.0 |
BayesianGLasso Bayesian Graphical Lasso | 0.2.0 | 0.2.0 |
BayesianLaterality Predict Brain Asymmetry Based on Handedness and Dichotic Listening | 0.1.2 | 0.1.2 |
BayesianTools General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics | 0.1.8 | 0.1.8 |
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 |
bayesLife Bayesian Projection of Life Expectancy | 5.2-0 | 5.2-0 |
bayeslincom Linear Combinations of Bayesian Posterior Samples | 1.3.0 | 1.3.0 |
BayesLN Bayesian Inference for Log-Normal Data | 0.2.10 | 0.2.10 |
BayesLogit PolyaGamma Sampling | 2.1 | 2.1 |
bayesloglin Bayesian Analysis of Contingency Table Data | 1.0.1 | 1.0.1 |
bayeslongitudinal Adjust Longitudinal Regression Models Using Bayesian Methodology | 0.1.0 | 0.1.0 |
bayesm Bayesian Inference for Marketing/Micro-Econometrics | 3.1-6 | 3.1-6 |
BayesMallows Bayesian Preference Learning with the Mallows Rank Model | 2.0.1 | 2.0.1 |
BayesMassBal Bayesian Data Reconciliation of Separation Processes | 1.1.0 | 1.1.0 |
bayesmeta Bayesian Random-Effects Meta-Analysis and Meta-Regression | 3.3 | 3.3 |
bayesmix Bayesian Mixture Models with JAGS | 0.7-6 | 0.7-6 |
bayesmove Non-Parametric Bayesian Analyses of Animal Movement | 0.2.1 | 0.2.1 |
bayesnec A Bayesian No-Effect- Concentration (NEC) Algorithm | 2.1.1.0 | 2.1.1.0 |
BayesPiecewiseICAR Hierarchical Bayesian Model for a Hazard Function | 0.2.1 | 0.2.1 |
bayesplot Plotting for Bayesian Models | 1.11.0 | 1.11.0 |
bayesQR Bayesian Quantile Regression | 2.4 | 2.4 |
BayesSAE Bayesian Analysis of Small Area Estimation | 1.0-2 | 1.0-2 |
bayesSurv Bayesian Survival Regression with Flexible Error and Random Effects Distributions | 3.6 | 3.6 |
bayestestR Understand and Describe Bayesian Models and Posterior Distributions | 0.13.1 | 0.13.1 |
bayesTFR Bayesian Fertility Projection | 7.4-2 | 7.4-2 |
BayesTools Tools for Bayesian Analyses | 0.2.16 | 0.2.16 |
BayesTree Bayesian Additive Regression Trees | 0.3-1.5 | 0.3-1.5 |
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 | 0.3-3 | 0.3-3 |
BAYSTAR On Bayesian Analysis of Threshold Autoregressive Models | 0.2-10 | 0.2-10 |
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 | 1.13 | 1.13 |
bbmle Tools for General Maximum Likelihood Estimation | 1.0.25.1 | 1.0.25.1 |
bbotk Black-Box Optimization Toolkit | 0.7.3 | 0.7.3 |
bbricks Bayesian Methods and Graphical Model Structures for Statistical Modeling | 0.1.4 | 0.1.4 |
bcaboot Bias Corrected Bootstrap Confidence Intervals | 0.2-3 | 0.2-3 |
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 | 2.4.5 | 2.4.5 |
BCEE The Bayesian Causal Effect Estimation Algorithm | 1.3.2 | 1.3.2 |
bcf Causal Inference for a Binary Treatment and Continuous Outcome using Bayesian Causal Forests | 1.3.1 | 1.3.1 |
BCHM Clinical Trial Calculation Based on BCHM Design | 1.00 | 1.00 |
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 | 1.3.2 | 1.3.2 |
bcrm Bayesian Continual Reassessment Method for Phase I Dose-Escalation Trials | 0.5.4 | 0.5.4 |
bcROCsurface Bias-Corrected Methods for Estimating the ROC Surface of Continuous Diagnostic Tests | 1.0-6 | 1.0-6 |
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 | 2.14.0 | 2.14.0 |
beadarray | ||
BeadDataPackR | ||
beakr A Minimalist Web Framework for R | 0.4.3 | 0.4.3 |
beanz Bayesian Analysis of Heterogeneous Treatment Effect | 2.4 | 2.4 |
BeastJar JAR Dependency for MCMC Using 'BEAST' | 1.10.6 | 1.10.6 |
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 |
behaviorchange Tools for Behavior Change Researchers and Professionals | 0.5.1 | 0.5.1 |
bench High Precision Timing of R Expressions | 1.1.2 | 1.1.2 |
benchden 28 benchmark densities from Berlinet/Devroye (1994) | 1.0.8 | 1.0.8 |
benchmarkme Crowd Sourced System Benchmarks | 1.0.8 | 1.0.8 |
benchmarkmeData Data Set for the 'benchmarkme' Package | 1.0.4 | 1.0.4 |
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 |
Bergm Bayesian Exponential Random Graph Models | 5.0.7 | 5.0.7 |
berryFunctions Function Collection Related to Plotting and Hydrology | 1.22.0 | 1.22.0 |
Bessel Computations and Approximations for Bessel Functions | 0.6-0 | 0.6-0 |
BEST Bayesian Estimation Supersedes the t-Test | 0.5.4 | 0.5.4 |
BetaBit Mini Games from Adventures of Beta and Bit | 2.2 | 2.2 |
betafunctions Functions for Working with Two- And Four-Parameter Beta Probability Distributions and Psychometric Analysis of Classifications | 1.8.1 | 1.8.1 |
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 |
bets.covid19 The BETS Model for Early Epidemic Data | 1.0.0 | 1.0.0 |
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 |
bfw Bayesian Framework for Computational Modeling | 0.4.2 | 0.4.2 |
bgmm Gaussian Mixture Modeling Algorithms and the Belief-Based Mixture Modeling | 1.8.5 | 1.8.5 |
bgumbel Bimodal Gumbel Distribution | 0.0.3 | 0.0.3 |
BGVAR Bayesian Global Vector Autoregressions | 2.5.5 | 2.5.5 |
bgw Bunch-Gay-Welsch Statistical Estimation | 0.1.2 | 0.1.2 |
BH Boost C++ Header Files | 1.84.0-0 | 1.84.0-0 |
BHH2 Useful Functions for Box, Hunter and Hunter II | 2016.05.31 | 2016.05.31 |
bhm Biomarker Threshold Models | 1.18 | 1.18 |
BiasedUrn Biased Urn Model Distributions | 2.0.11 | 2.0.11 |
bibliometrix Comprehensive Science Mapping Analysis | 4.0.0 | 4.0.0 |
bibliometrixData Bibliometrix Example Datasets | 0.3.0 | 0.3.0 |
bibtex Bibtex Parser | 0.5.1 | 0.5.1 |
biclust BiCluster Algorithms | 2.0.3.1 | 2.0.3.1 |
biclustermd Biclustering with Missing Data | 0.2.3 | 0.2.3 |
bidask Efficient Estimation of Bid-Ask Spreads from Open, High, Low, and Close Prices | 2.0.2 | 2.0.2 |
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 |
bigchess Read, Write, Manipulate, Explore Chess PGN Files and R API to UCI Chess Engines | 1.9.1 | 1.9.1 |
bigD Flexibly Format Dates and Times to a Given Locale | 0.2.0 | 0.2.0 |
bigdatadist Distances for Machine Learning and Statistics in the Context of Big Data | 1.1 | 1.1 |
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 | 4.6.4 | 4.6.4 |
bigmemory.sri A Shared Resource Interface for Bigmemory Project Packages | 0.1.8 | 0.1.8 |
bignum Arbitrary-Precision Integer and Floating-Point Mathematics | 0.3.2 | 0.3.2 |
bigparallelr Easy Parallel Tools | 0.3.2 | 0.3.2 |
bigreadr Read Large Text Files | 0.2.5 | 0.2.5 |
bigrquery An Interface to Google's 'BigQuery' 'API' | 1.5.0 | 1.5.0 |
bigsplines Smoothing Splines for Large Samples | 1.1-1 | 1.1-1 |
bigstatsr Statistical Tools for Filebacked Big Matrices | 1.5.12 | 1.5.12 |
bigtime Sparse Estimation of Large Time Series Models | 0.2.3 | 0.2.3 |
BigVAR Dimension Reduction Methods for Multivariate Time Series | 1.1.2 | 1.1.2 |
bimets Time Series and Econometric Modeling | 3.0.2 | 3.0.2 |
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 |
binseqtest Exact Binary Sequential Designs and Analysis | 1.0.4 | 1.0.4 |
bio3d Biological Structure Analysis | 2.4-4 | 2.4-4 |
Biobase | 2.62.0 | 2.62.0 |
BiocFileCache | 2.10.1 | 2.10.1 |
BiocGenerics | 0.48.1 | 0.48.1 |
BiocIO | 1.12.0 | 1.12.0 |
BiocManager Access the Bioconductor Project Package Repository | 1.30.22 | 1.30.22 |
BiocNeighbors | 1.20.0 | 1.20.0 |
BiocParallel | 1.36.0 | 1.36.0 |
BiocSingular | 1.14.0 | 1.14.0 |
BiocVersion | 3.16.0 | 3.16.0 |
BiodiversityR Package for Community Ecology and Suitability Analysis | 2.15-2 | 2.15-2 |
bioinactivation Mathematical Modelling of (Dynamic) Microbial Inactivation | 1.2.3 | 1.2.3 |
biomaRt | 2.54.0 | 2.54.0 |
Bios2cor From Biological Sequences and Simulations to Correlation Analysis | 2.2 | 2.2 |
Biostrings | 2.70.1 | 2.70.1 |
biotic Calculation of Freshwater Biotic Indices | 0.1.2 | 0.1.2 |
bipartite Visualising Bipartite Networks and Calculating Some (Ecological) Indices | 2.19 | 2.19 |
bipd Bayesian Individual Patient Data Meta-Analysis using 'JAGS' | 0.3 | 0.3 |
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.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 | 1.0.15 | 1.0.15 |
bjscrapeR An API Wrapper for the Bureau of Justice Statistics (BJS) | 0.1.0 | 0.1.0 |
bkmr Bayesian Kernel Machine Regression | 0.2.2 | 0.2.2 |
blaise Read and Write FWF Files in the 'Blaise' Format | 1.3.11 | 1.3.11 |
blastula Easily Send HTML Email Messages | 0.3.4 | 0.3.4 |
blavaan Bayesian Latent Variable Analysis | 0.4-6 | 0.4-6 |
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 |
blocklength Select an Optimal Block-Length to Bootstrap Dependent Data (Block Bootstrap) | 0.1.5 | 0.1.5 |
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 |
blogdown Create Blogs and Websites with R Markdown | 1.17 | 1.17 |
BLOQ Impute and Analyze Data with BLOQ Observations | 0.1-1 | 0.1-1 |
blotter | 0.16.0 | 0.16.0 |
BLR Bayesian Linear Regression | 1.6 | 1.6 |
bluster | 1.12.0 | 1.12.0 |
BMA Bayesian Model Averaging | 3.18.17 | 3.18.17 |
BMAmevt Multivariate Extremes: Bayesian Estimation of the Spectral Measure | 1.0.5 | 1.0.5 |
bmgarch Bayesian Multivariate GARCH Models | 2.0.0 | 2.0.0 |
BMisc Miscellaneous Functions for Panel Data, Quantiles, and Printing Results | 1.4.5 | 1.4.5 |
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 |
BMTAR Bayesian Approach for MTAR Models with Missing Data | 0.1.1 | 0.1.1 |
bnclassify Learning Discrete Bayesian Network Classifiers from Data | 0.4.7 | 0.4.7 |
bnlearn Bayesian Network Structure Learning, Parameter Learning and Inference | 4.9.1 | 4.9.1 |
bnma Bayesian Network Meta-Analysis using 'JAGS' | 1.5.1 | 1.5.1 |
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 | 2.2.3 | 2.2.3 |
bnstruct Bayesian Network Structure Learning from Data with Missing Values | 1.0.15 | 1.0.15 |
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 |
Bolstad Functions for Elementary Bayesian Inference | 0.2-41 | 0.2-41 |
Bolstad2 Bolstad Functions | 1.0-29 | 1.0-29 |
bookdown Authoring Books and Technical Documents with R Markdown | 0.37 | 0.37 |
BoolNet Construction, Simulation and Analysis of Boolean Networks | 2.1.5 | 2.1.5 |
Boom Bayesian Object Oriented Modeling | 0.9.14 | 0.9.14 |
BoomSpikeSlab MCMC for Spike and Slab Regression | 1.2.6 | 1.2.6 |
boot Bootstrap Functions (Originally by Angelo Canty for S) | 1.3-28.1 | 1.3-28.1 |
boot.heterogeneity A Bootstrap-Based Heterogeneity Test for Meta-Analysis | 1.1.5 | 1.1.5 |
bootImpute Bootstrap Inference for Multiple Imputation | 1.2.1 | 1.2.1 |
bootnet Bootstrap Methods for Various Network Estimation Routines | 1.5.6 | 1.5.6 |
BootPR Bootstrap Prediction Intervals and Bias-Corrected Forecasting | 1.0 | 1.0 |
bootstrap Functions for the Book "An Introduction to the Bootstrap" | 2019.6 | 2019.6 |
bootUR Bootstrap Unit Root Tests | 1.0.3 | 1.0.3 |
Boptbd Bayesian Optimal Block Designs | 1.0.5 | 1.0.5 |
borrowr Estimate Causal Effects with Borrowing Between Data Sources | 0.2.0 | 0.2.0 |
Boruta Wrapper Algorithm for All Relevant Feature Selection | 8.0.0 | 8.0.0 |
boussinesq Analytic Solutions for (Ground-Water) Boussinesq Equation | 1.0.6 | 1.0.6 |
boutliers Outlier Detection and Influence Diagnostics for Meta-Analysis | 1.1-2 | 1.1-2 |
boxr Interface for the 'Box.com API' | 0.3.6 | 0.3.6 |
bpbounds Nonparametric Bounds for the Average Causal Effect Due to Balke and Pearl and Extensions | 0.1.5 | 0.1.5 |
bpca Biplot of Multivariate Data Based on Principal Components Analysis | 1.3-6 | 1.3-6 |
bpcp Beta Product Confidence Procedure for Right Censored Data | 1.4.2 | 1.4.2 |
bqtl Bayesian QTL Mapping Toolkit | 1.0-36 | 1.0-36 |
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 |
brandwatchR 'Brandwatch' API to R | 0.3.0 | 0.3.0 |
breakDown Model Agnostic Explainers for Individual Predictions | 0.2.1 | 0.2.1 |
breakfast Methods for Fast Multiple Change-Point Detection and Estimation | 2.3 | 2.3 |
bReeze Functions for Wind Resource Assessment | 0.4-3 | 0.4-3 |
brew Templating Framework for Report Generation | 1.0-10 | 1.0-10 |
brglm Bias Reduction in Binomial-Response Generalized Linear Models | 0.7.2 | 0.7.2 |
brglm2 Bias Reduction in Generalized Linear Models | 0.9.2 | 0.9.2 |
bridgedist An Implementation of the Bridge Distribution with Logit-Link as in Wang and Louis (2003) | 0.1.2 | 0.1.2 |
bridgesampling Bridge Sampling for Marginal Likelihoods and Bayes Factors | 1.1-2 | 1.1-2 |
brio Basic R Input Output | 1.1.4 | 1.1.4 |
brms Bayesian Regression Models using 'Stan' | 2.20.4 | 2.20.4 |
brnn Bayesian Regularization for Feed-Forward Neural Networks | 0.9.3 | 0.9.3 |
Brobdingnag Very Large Numbers in R | 1.2-9 | 1.2-9 |
brolgar Browse Over Longitudinal Data Graphically and Analytically in R | 1.0.0 | 1.0.0 |
broman Karl Broman's R Code | 0.80 | 0.80 |
broom Convert Statistical Objects into Tidy Tibbles | 1.0.5 | 1.0.5 |
broom.helpers Helpers for Model Coefficients Tibbles | 1.14.0 | 1.14.0 |
broom.mixed Tidying Methods for Mixed Models | 0.2.9.4 | 0.2.9.4 |
broomExtra Enhancements for 'broom' and 'easystats' Package Families | 4.3.2 | 4.3.2 |
brotli A Compression Format Optimized for the Web | 1.3.0 | 1.3.0 |
brxx Bayesian Test Reliability Estimation | 0.1.2 | 0.1.2 |
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 |
BSBT The Bayesian Spatial Bradley--Terry Model | 1.2.1 | 1.2.1 |
BSDA Basic Statistics and Data Analysis | 1.2.1 | 1.2.1 |
bshazard Nonparametric Smoothing of the Hazard Function | 1.1 | 1.1 |
bslib Custom 'Bootstrap' 'Sass' Themes for 'shiny' and 'rmarkdown' | 0.6.1 | 0.6.1 |
BsMD Bayes Screening and Model Discrimination | 2023.920 | 2023.920 |
bspec Bayesian Spectral Inference | 1.6 | 1.6 |
bspm Bridge to System Package Manager | 0.5.5 | 0.5.5 |
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 | 2.0.2 | 2.0.2 |
BSSprep Whitening Data as Preparation for Blind Source Separation | 0.1 | 0.1 |
bst Gradient Boosting | 0.3-24 | 0.3-24 |
bsts Bayesian Structural Time Series | 0.9.10 | 0.9.10 |
BTdecayLasso Bradley-Terry Model with Exponential Time Decayed Log-Likelihood and Adaptive Lasso | 0.1.0 | 0.1.0 |
BTLLasso Modelling Heterogeneity in Paired Comparison Data | 0.1-12 | 0.1-12 |
BTM Biterm Topic Models for Short Text | 0.3.7 | 0.3.7 |
bujar Buckley-James Regression for Survival Data with High-Dimensional Covariates | 0.2-11 | 0.2-11 |
bundesbank Download Data from Bundesbank | 0.1-11 | 0.1-11 |
BurStFin Burns Statistics Financial | 1.3 | 1.3 |
BurStMisc Burns Statistics Miscellaneous | 1.1 | 1.1 |
butcher Model Butcher | 0.3.3 | 0.3.3 |
BuyseTest Generalized Pairwise Comparisons | 2.4.0 | 2.4.0 |
BVAR Hierarchical Bayesian Vector Autoregression | 1.0.4 | 1.0.4 |
bvartools Bayesian Inference of Vector Autoregressive and Error Correction Models | 0.2.4 | 0.2.4 |
bvls The Stark-Parker algorithm for bounded-variable least squares | 1.4 | 1.4 |
BWStest Baumgartner Weiss Schindler Test of Equal Distributions | 0.2.3 | 0.2.3 |
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 | 1.0.8 | 1.0.8 |
cacIRT Classification Accuracy and Consistency under Item Response Theory | 1.4 | 1.4 |
CaDENCE Conditional Density Estimation Network Construction and Evaluation | 1.2.5 | 1.2.5 |
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 | 1.6-1 | 1.6-1 |
calculus High Dimensional Numerical and Symbolic Calculus | 1.0.1 | 1.0.1 |
CALIBERrfimpute Multiple Imputation Using MICE and Random Forest | 1.0-6 | 1.0-6 |
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 |
CalibratR Mapping ML Scores to Calibrated Predictions | 0.1.2 | 0.1.2 |
callr Call R from R | 3.7.3 | 3.7.3 |
CAMAN Finite Mixture Models and Meta-Analysis Tools - Based on C.A.MAN | 0.78 | 0.78 |
cancensus Access, Retrieve, and Work with Canadian Census Data and Geography | 0.5.6 | 0.5.6 |
candisc Visualizing Generalized Canonical Discriminant and Canonical Correlation Analysis | 0.8-6 | 0.8-6 |
CANSIM2R Directly Extracts Complete CANSIM Data Tables | 1.14.1 | 1.14.1 |
captr Client for the Captricity API | 0.3.0 | 0.3.0 |
car Companion to Applied Regression | 3.1-2 | 3.1-2 |
caracas Computer Algebra | 2.1.1 | 2.1.1 |
caRamel Automatic Calibration by Evolutionary Multi Objective Algorithm | 1.3 | 1.3 |
CARBayes Spatial Generalised Linear Mixed Models for Areal Unit Data | 6.1 | 6.1 |
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 | 4.0 | 4.0 |
carData Companion to Applied Regression Data Sets | 3.0-5 | 3.0-5 |
care High-Dimensional Regression and CAR Score Variable Selection | 1.1.11 | 1.1.11 |
caret Classification and Regression Training | 6.0-94 | 6.0-94 |
carfima Continuous-Time Fractionally Integrated ARMA Process for Irregularly Spaced Long-Memory Time Series Data | 2.0.2 | 2.0.2 |
caribou Estimation of Caribou Abundance Based on Radio Telemetry Data | 1.1-1 | 1.1-1 |
Carlson Carlson Elliptic Integrals and Incomplete Elliptic Integrals | 3.0.0 | 3.0.0 |
cartogram Create Cartograms with R | 0.3.0 | 0.3.0 |
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 |
CaseBasedReasoning Case Based Reasoning | 0.3 | 0.3 |
CAST 'caret' Applications for Spatial-Temporal Models | 0.9.0 | 0.9.0 |
cat Analysis and Imputation of Categorical-Variable Datasets with Missing Values | 0.0-9 | 0.0-9 |
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 |
causact Accelerated Bayesian Analytics with DAGs | 0.5.3 | 0.5.3 |
causaldata Example Data Sets for Causal Inference Textbooks | 0.1.3 | 0.1.3 |
causaldrf Estimating Causal Dose Response Functions | 0.4.2 | 0.4.2 |
causaleffect Deriving Expressions of Joint Interventional Distributions and Transport Formulas in Causal Models | 1.3.13 | 1.3.13 |
CausalGAM Estimation of Causal Effects with Generalized Additive Models | 0.1-4 | 0.1-4 |
CausalGPS Matching on Generalized Propensity Scores with Continuous Exposures | 0.4.1 | 0.4.1 |
CausalImpact Inferring Causal Effects using Bayesian Structural Time-Series Models | 1.3.0 | 1.3.0 |
CausalMBSTS MBSTS Models for Causal Inference and Forecasting | 0.1.1 | 0.1.1 |
causaloptim An Interface to Specify Causal Graphs and Compute Bounds on Causal Effects | 0.9.8 | 0.9.8 |
causalsens Selection Bias Approach to Sensitivity Analysis for Causal Effects | 0.1.2 | 0.1.2 |
causalweight Estimation Methods for Causal Inference Based on Inverse Probability Weighting | 1.1.0 | 1.1.0 |
CAvariants Correspondence Analysis Variants | 6.0 | 6.0 |
cba Clustering for Business Analytics | 0.2-23 | 0.2-23 |
cbinom Continuous Analog of a Binomial Distribution | 1.6 | 1.6 |
CBPS Covariate Balancing Propensity Score | 0.23 | 0.23 |
cbsodataR Statistics Netherlands (CBS) Open Data API Client | 1.0.1 | 1.0.1 |
cccp Cone Constrained Convex Problems | 0.3-1 | 0.3-1 |
cclust Convex Clustering Methods and Clustering Indexes | 0.6-26 | 0.6-26 |
CCP Significance Tests for Canonical Correlation Analysis (CCA) | 1.2 | 1.2 |
cdata Fluid Data Transformations | 1.2.0 | 1.2.0 |
cdlTools Tools to Download and Work with USDA Cropscape Data | 0.15 | 0.15 |
CDM Cognitive Diagnosis Modeling | 8.2-6 | 8.2-6 |
CDNmoney Components of Canadian Monetary and Credit Aggregates | 2012.4-2 | 2012.4-2 |
cds Constrained Dual Scaling for Detecting Response Styles | 1.0.3 | 1.0.3 |
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 | 2.5.3 | 2.5.3 |
cem Coarsened Exact Matching | 1.1.31 | 1.1.31 |
censReg Censored Regression (Tobit) Models | 0.5-36 | 0.5-36 |
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 |
CEoptim Cross-Entropy R Package for Optimization | 1.3 | 1.3 |
ceterisParibus Ceteris Paribus Profiles | 0.4.2 | 0.4.2 |
cfbfastR Access College Football Play by Play Data | 1.9.0 | 1.9.0 |
CFC Cause-Specific Framework for Competing-Risk Analysis | 1.2.0 | 1.2.0 |
cfdecomp Counterfactual Decomposition: MC Integration of the G-Formula | 0.4.0 | 0.4.0 |
cfma Causal Functional Mediation Analysis | 1.0 | 1.0 |
cgdsr R-Based API for Accessing the MSKCC Cancer Genomics Data Server (CGDS) | 1.3.0 | 1.3.0 |
cglasso Conditional Graphical LASSO for Gaussian Graphical Models with Censored and Missing Values | 2.0.6 | 2.0.6 |
ChainLadder Statistical Methods and Models for Claims Reserving in General Insurance | 0.2.18 | 0.2.18 |
chandwich Chandler-Bate Sandwich Loglikelihood Adjustment | 1.1.6 | 1.1.6 |
changepoint Methods for Changepoint Detection | 2.2.4 | 2.2.4 |
changepoint.geo Geometrically Inspired Multivariate Changepoint Detection | 1.0.2 | 1.0.2 |
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 |
checkmate Fast and Versatile Argument Checks | 2.3.1 | 2.3.1 |
checkpoint Install Packages from Snapshots on the Checkpoint Server for Reproducibility | 1.0.2 | 1.0.2 |
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 | 1.0.4 | 1.0.4 |
cherryblossom Cherry Blossom Run Race Results | 0.1.0 | 0.1.0 |
chess Read, Write, Create and Explore Chess Games | 1.0.1 | 1.0.1 |
chessR Functions to Extract, Clean and Analyse Online Chess Game Data | 1.5.2 | 1.5.2 |
chilemapas Mapas de las Divisiones Politicas y Administrativas de Chile (Maps of the Political and Administrative Divisions of Chile) | 0.3.0 | 0.3.0 |
chk Check User-Supplied Function Arguments | 0.9.1 | 0.9.1 |
CHNOSZ Thermodynamic Calculations and Diagrams for Geochemistry | 2.0.0 | 2.0.0 |
choiceDes Design Functions for Choice Studies | 0.9-3 | 0.9-3 |
CholWishart Cholesky Decomposition of the Wishart Distribution | 1.1.2 | 1.1.2 |
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 |
chromote Headless Chrome Web Browser Interface | 0.1.0 | 0.1.0 |
chron Chronological Objects which Can Handle Dates and Times | 2.3-61 | 2.3-61 |
CHsharp Choi and Hall Style Data Sharpening | 0.4 | 0.4 |
chyper Functions for Conditional Hypergeometric Distributions | 0.3.1 | 0.3.1 |
CIAAWconsensus Isotope Ratio Meta-Analysis | 1.3 | 1.3 |
CIEE Estimating and Testing Direct Effects in Directed Acyclic Graphs using Estimating Equations | 0.1.1 | 0.1.1 |
cifti Toolbox for Connectivity Informatics Technology Initiative ('CIFTI') Files | 0.4.5 | 0.4.5 |
cinterpolate Interpolation From C | 1.0.1 | 1.0.1 |
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 | 0.5-0 | 0.5-0 |
circumplex Analysis and Visualization of Circular Data | 0.3.10 | 0.3.10 |
cit Causal Inference Test | 2.3.1 | 2.3.1 |
citationchaser Perform Forward and Backwards Chasing in Evidence Syntheses | 0.0.4 | 0.0.4 |
ciTools Confidence or Prediction Intervals, Quantiles, and Probabilities for Statistical Models | 0.6.1 | 0.6.1 |
cjoint AMCE Estimator for Conjoint Experiments | 2.1.1 | 2.1.1 |
CKAT Composite Kernel Association Test for Pharmacogenetics Studies | 0.1.0 | 0.1.0 |
Ckmeans.1d.dp Optimal, Fast, and Reproducible Univariate Clustering | 4.3.4 | 4.3.4 |
clarifai Access to Clarifai API | 0.4.2 | 0.4.2 |
class Functions for Classification | 7.3-22 | 7.3-22 |
classInt Choose Univariate Class Intervals | 0.4-10 | 0.4-10 |
cli Helpers for Developing Command Line Interfaces | 3.6.2 | 3.6.2 |
cliapp Create Rich Command Line Applications | 0.1.1 | 0.1.1 |
clifford Arbitrary Dimensional Clifford Algebras | 1.0-8 | 1.0-8 |
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) | 4.0.0 | 4.0.0 |
climdex.pcic PCIC Implementation of Climdex Routines | 1.1-11 | 1.1-11 |
clime Constrained L1-Minimization for Inverse (Covariance) Matrix Estimation | 0.5.0 | 0.5.0 |
climextRemes Tools for Analyzing Climate Extremes | 0.3.1 | 0.3.1 |
clinfun Clinical Trial Design and Data Analysis Functions | 1.1.5 | 1.1.5 |
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 | 0.7.0 | 0.7.0 |
cloudml Interface to the Google Cloud Machine Learning Platform | 0.6.1 | 0.6.1 |
clubSandwich Cluster-Robust (Sandwich) Variance Estimators with Small-Sample Corrections | 0.5.10 | 0.5.10 |
clue Cluster Ensembles | 0.3-65 | 0.3-65 |
cluster "Finding Groups in Data": Cluster Analysis Extended Rousseeuw et al. | 2.1.3 | 2.1.3 |
clusterCrit Clustering Indices | 1.3.0 | 1.3.0 |
clusteredinterference Causal Effects from Observational Studies with Clustered Interference | 1.0.1 | 1.0.1 |
clusterGeneration Random Cluster Generation (with Specified Degree of Separation) | 1.3.8 | 1.3.8 |
clustermq Evaluate Function Calls on HPC Schedulers (LSF, SGE, SLURM, PBS/Torque) | 0.9.3 | 0.9.3 |
clusterPower Power Calculations for Cluster-Randomized and Cluster-Randomized Crossover Trials | 0.7.0 | 0.7.0 |
clusterProfiler | 4.10.0 | 4.10.0 |
ClusterR Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans, K-Medoids and Affinity Propagation Clustering | 1.3.2 | 1.3.2 |
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 | 0.51-3 | 0.51-3 |
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 | 0.3-14 | 0.3-14 |
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 | 0.3-2.4 | 0.3-2.4 |
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 |
CMF Collective Matrix Factorization | 1.0.3 | 1.0.3 |
cmfrec Collective Matrix Factorization for Recommender Systems | 3.5.1-3 | 3.5.1-3 |
CMLS Constrained Multivariate Least Squares | 1.0-1 | 1.0-1 |
cmm Categorical Marginal Models | 1.0 | 1.0 |
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 |
cmstatr Statistical Methods for Composite Material Data | 0.9.1 | 0.9.1 |
cmvnorm The Complex Multivariate Gaussian Distribution | 1.0-7 | 1.0-7 |
cna Causal Modeling with Coincidence Analysis | 3.5.6 | 3.5.6 |
cncaGUI Canonical Non-Symmetrical Correspondence Analysis in R | 1.1 | 1.1 |
cNORM Continuous Norming | 3.0.4 | 3.0.4 |
coalescentMCMC MCMC Algorithms for the Coalescent | 0.4-4 | 0.4-4 |
coalitions Bayesian "Now-Cast" Estimation of Event Probabilities in Multi-Party Democracies | 0.6.24 | 0.6.24 |
coarseDataTools Analysis of Coarsely Observed Data | 0.6-6 | 0.6-6 |
cobalt Covariate Balance Tables and Plots | 4.5.3 | 4.5.3 |
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 | 1.2.2 | 1.2.2 |
CoImp Copula Based Imputation Method | 1.0 | 1.0 |
coin Conditional Inference Procedures in a Permutation Test Framework | 1.4-3 | 1.4-3 |
cointReg Parameter Estimation and Inference in a Cointegrating Regression | 0.2.0 | 0.2.0 |
cold Count Longitudinal Data | 2.0-3 | 2.0-3 |
colf Constrained Optimization on Linear Function | 0.1.3 | 0.1.3 |
collapse Advanced and Fast Data Transformation | 2.0.6 | 2.0.6 |
collapsibleTree Interactive Collapsible Tree Diagrams using 'D3.js' | 0.1.8 | 0.1.8 |
collections High Performance Container Data Types | 0.3.5 | 0.3.5 |
CollocInfer Collocation Inference for Dynamic Systems | 1.0.4 | 1.0.4 |
colorr Color Palettes for EPL, MLB, NBA, NHL, and NFL Teams | 1.0.0 | 1.0.0 |
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 | 1.3.0 | 1.3.0 |
colourvalues Assigns Colours to Values | 0.3.9 | 0.3.9 |
combinat combinatorics utilities | 0.0-8 | 0.0-8 |
combinedevents Calculate Scores and Marks for Track and Field Combined Events | 0.1.1 | 0.1.1 |
CombinS Construction Methods of some Series of PBIB Designs | 1.1-1 | 1.1-1 |
CommonJavaJars Useful Libraries for Building a Java Based GUI under R | 1.0-6 | 1.0-6 |
commonmark High Performance CommonMark and Github Markdown Rendering in R | 1.9.1 | 1.9.1 |
compare Comparing Objects for Differences | 0.2-6 | 0.2-6 |
compareC Compare Two Correlated C Indices with Right-Censored Survival Outcome | 1.3.2 | 1.3.2 |
CompareCausalNetworks Interface to Diverse Estimation Methods of Causal Networks | 0.2.6.2 | 0.2.6.2 |
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 | 4.4.1 | 4.4.1 |
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 | 6.6 | 6.6 |
compositions Compositional Data Analysis | 2.0-8 | 2.0-8 |
compound.Cox Univariate Feature Selection and Compound Covariate for Predicting Survival | 3.30 | 3.30 |
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 |
compute.es Compute Effect Sizes | 0.2-5 | 0.2-5 |
concreg Concordance Regression | 0.7 | 0.7 |
concurve Computes & Plots Compatibility (Confidence), Surprisal, & Likelihood Distributions | 2.7.7 | 2.7.7 |
condGEE Parameter Estimation in Conditional GEE for Recurrent Event Gap Times | 0.2.0 | 0.2.0 |
CondIndTests Nonlinear Conditional Independence Tests | 0.1.5 | 0.1.5 |
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 | 1.17 | 1.17 |
conf.design Construction of factorial designs | 2.0.0 | 2.0.0 |
config Manage Environment Specific Configuration Values | 0.3.2 | 0.3.2 |
confintr Confidence Intervals | 1.0.2 | 1.0.2 |
conflicted An Alternative Conflict Resolution Strategy | 1.2.0 | 1.2.0 |
confoundr Diagnostics for Confounding of Time-Varying and Other Joint Exposures | 1.2 | 1.2 |
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 |
conquer Convolution-Type Smoothed Quantile Regression | 1.3.3 | 1.3.3 |
conquestr An R Package to Extend 'ACER ConQuest' | 1.1.1 | 1.1.1 |
ConsRank Compute the Median Ranking(s) According to the Kemeny's Axiomatic Approach | 2.1.4 | 2.1.4 |
constants Reference on Constants, Units and Uncertainty | 1.0.1 | 1.0.1 |
contactdata Social Contact Matrices for 177 Countries | 1.0.0 | 1.0.0 |
container Extending Base 'R' Lists | 1.0.2 | 1.0.2 |
contfrac Continued Fractions | 1.1-12 | 1.1-12 |
conting Bayesian Analysis of Contingency Tables | 1.7 | 1.7 |
controlTest Quantile Comparison for Two-Sample Right-Censored Survival Data | 1.1.0 | 1.1.0 |
convergEU Monitoring Convergence of EU Countries | 0.5.4 | 0.5.4 |
convey Income Concentration Analysis with Complex Survey Samples | 1.0.0 | 1.0.0 |
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 | 2.2.3 | 2.2.3 |
cops Cluster Optimized Proximity Scaling | 1.3-1 | 1.3-1 |
copula Multivariate Dependence with Copulas | 1.1-3 | 1.1-3 |
copulaData Data Sets for Copula Modeling | 0.0-1 | 0.0-1 |
CopulaDTA Copula Based Bivariate Beta-Binomial Model for Diagnostic Test Accuracy Studies | 1.0.0 | 1.0.0 |
copulaedas Estimation of Distribution Algorithms Based on Copulas | 1.4.3 | 1.4.3 |
cordillera Calculation of the OPTICS Cordillera | 1.0-0 | 1.0-0 |
CORElearn Classification, Regression and Feature Evaluation | 1.57.3 | 1.57.3 |
cornet Elastic Net with Dichotomised Outcomes | 0.0.9 | 0.0.9 |
coro 'Coroutines' for R | 1.0.3 | 1.0.3 |
corona Coronavirus ('Rona') Data Exploration | 0.3.0 | 0.3.0 |
coronavirus The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Dataset | 0.4.1 | 0.4.1 |
corpcor Efficient Estimation of Covariance and (Partial) Correlation | 1.6.10 | 1.6.10 |
corpora Statistics and Data Sets for Corpus Frequency Data | 0.6 | 0.6 |
corporaexplorer A 'Shiny' App for Exploration of Text Collections | 0.8.6 | 0.8.6 |
correlation Methods for Correlation Analysis | 0.8.4 | 0.8.4 |
corrplot Visualization of a Correlation Matrix | 0.92 | 0.92 |
cort Some Empiric and Nonparametric Copula Models | 0.3.2 | 0.3.2 |
cosa Bound Constrained Optimal Sample Size Allocation | 2.1.0 | 2.1.0 |
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 |
CoSMoS Complete Stochastic Modelling Solution | 2.1.0 | 2.1.0 |
costat Time Series Costationarity Determination | 2.4.1 | 2.4.1 |
Counterfactual Estimation and Inference Methods for Counterfactual Analysis | 1.2 | 1.2 |
countrycode Convert Country Names and Country Codes | 1.5.0 | 1.5.0 |
COVID19 R Interface to COVID-19 Data Hub | 3.0.3 | 3.0.3 |
covid19.analytics Load and Analyze Live Data from the COVID-19 Pandemic | 2.1.3.3 | 2.1.3.3 |
covid19br Brazilian COVID-19 Pandemic Data | 0.1.8 | 0.1.8 |
covid19dbcand Selected 'Drugbank' Drugs for COVID-19 Treatment Related Data in R Format | 0.1.1 | 0.1.1 |
covid19france Cases of COVID-19 in France | 0.1.0 | 0.1.0 |
covid19italy The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Italy Dataset | 0.3.1 | 0.3.1 |
covid19sf The Covid19 San Francisco Dataset | 0.1.2 | 0.1.2 |
covid19swiss COVID-19 Cases in Switzerland and Principality of Liechtenstein | 0.1.0 | 0.1.0 |
covid19us Cases of COVID-19 in the United States | 0.1.9 | 0.1.9 |
CovidMutations Mutation Analysis Toolkit for COVID-19 (Coronavirus Disease 2019) | 0.1.3 | 0.1.3 |
covLCA Latent Class Models with Covariate Effects on Underlying and<U+000a>Measured Variables | 1.0 | 1.0 |
covr Test Coverage for Packages | 3.6.4 | 3.6.4 |
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' | 1.1.3 | 1.1.3 |
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 | 1.13.4 | 1.13.4 |
coxphw Weighted Estimation in Cox Regression | 4.0.3 | 4.0.3 |
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 |
cpk Clinical Pharmacokinetics | 1.3-1 | 1.3-1 |
cplm Compound Poisson Linear Models | 0.7-12 | 0.7-12 |
cpp11 A C++11 Interface for R's C Interface | 0.4.7 | 0.4.7 |
Cprob The Conditional Probability Function of a Competing Event | 1.4.1 | 1.4.1 |
CRAC Cosmology R Analysis Code | 1.0 | 1.0 |
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 | 1.1-2 | 1.1-2 |
credentials Tools for Managing SSH and Git Credentials | 2.0.1 | 2.0.1 |
credule Credit Default Swap Functions | 0.1.4 | 0.1.4 |
crfsuite Conditional Random Fields for Labelling Sequential Data in Natural Language Processing | 0.4.2 | 0.4.2 |
cricketdata International Cricket Data | 0.2.3 | 0.2.3 |
cricketr Analyze Cricketers and Cricket Teams Based on ESPN Cricinfo Statsguru | 0.0.26 | 0.0.26 |
crimCV Group-Based Modelling of Longitudinal Data | 1.0.0 | 1.0.0 |
CRM Continual Reassessment Method (CRM) for Phase I Clinical Trials | 1.2.4 | 1.2.4 |
crmPack Object-Oriented Implementation of CRM Designs | 1.0.4 | 1.0.4 |
crossdes Construction of Crossover Designs | 1.1-2 | 1.1-2 |
Crossover Analysis and Search of Crossover Designs | 0.1-21 | 0.1-21 |
crosstalk Inter-Widget Interactivity for HTML Widgets | 1.2.1 | 1.2.1 |
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 |
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 | 1.4.0 | 1.4.0 |
crunch Crunch.io Data Tools | 1.30.2 | 1.30.2 |
crunchy Shiny Apps on Crunch | 0.3.3 | 0.3.3 |
csci Current Status Confidence Intervals | 0.9.3 | 0.9.3 |
CSGo Collecting Counter Strike Global Offensive Data | 0.6.7 | 0.6.7 |
cshapes The CShapes 2.0 Dataset and Utilities | 2.0 | 2.0 |
csn Closed Skew-Normal Distribution | 1.1.3 | 1.1.3 |
csodata Download Data from the CSO 'PxStat' API | 1.4.2 | 1.4.2 |
cstab Selection of Number of Clusters via Normalized Clustering Instability | 0.2-2 | 0.2-2 |
ctmcd Estimating the Parameters of a Continuous-Time Markov Chain from Discrete-Time Data | 1.4.1 | 1.4.1 |
ctmcmove Modeling Animal Movement with Continuous-Time Discrete-Space Markov Chains | 1.2.9 | 1.2.9 |
ctmle Collaborative Targeted Maximum Likelihood Estimation | 0.1.2 | 0.1.2 |
ctmm Continuous-Time Movement Modeling | 1.2.0 | 1.2.0 |
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 | 2.1.0 | 2.1.0 |
cubble A Vector Spatio-Temporal Data Structure for Data Analysis | 0.3.0 | 0.3.0 |
cubelyr A Data Cube 'dplyr' Backend | 1.0.2 | 1.0.2 |
Cubist Rule- And Instance-Based Regression Modeling | 0.4.2.1 | 0.4.2.1 |
curl A Modern and Flexible Web Client for R | 5.0.2 | 5.0.2 |
currentSurvival Estimation of CCI and CLFS Functions | 1.1 | 1.1 |
cutoffR CUTOFF: A Spatio-temporal Imputation Method | 1.0 | 1.0 |
cutpointr Determine and Evaluate Optimal Cutpoints in Binary Classification Tasks | 1.1.1 | 1.1.1 |
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 |
cvTools Cross-validation tools for regression models | 0.3.2 | 0.3.2 |
CVXR Disciplined Convex Optimization | 1.0-11 | 1.0-11 |
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 |
Cyclops Cyclic Coordinate Descent for Logistic, Poisson and Survival Analysis | 3.4.0 | 3.4.0 |
cytofan Plot Fan Plots for Cytometry Data using 'ggplot2' | 0.1.0 | 0.1.0 |
d3Network Tools for creating D3 JavaScript network, tree, dendrogram, and<U+000a>Sankey graphs from R | 0.5.2.1 | 0.5.2.1 |
DAAG Data Analysis and Graphics Data and Functions | 1.25.4 | 1.25.4 |
daarem Damped Anderson Acceleration with Epsilon Monotonicity for Accelerating EM-Like Monotone Algorithms | 0.7 | 0.7 |
dae Functions Useful in the Design and ANOVA of Experiments | 3.2.21 | 3.2.21 |
daewr Design and Analysis of Experiments with R | 1.2-11 | 1.2-11 |
dagitty Graphical Analysis of Structural Causal Models | 0.3-1 | 0.3-1 |
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 |
dash An Interface to the Dash Ecosystem for Authoring Reactive Web Applications | 0.9.4 | 0.9.4 |
data.table Extension of `data.frame` | 1.15.0 | 1.15.0 |
data.tree General Purpose Hierarchical Data Structure | 1.1.0 | 1.1.0 |
DatabionicSwarm Swarm Intelligence for Self-Organized Clustering | 1.2.1 | 1.2.1 |
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 | 2.7.14 | 2.7.14 |
datarobot 'DataRobot' Predictive Modeling API | 2.18.5 | 2.18.5 |
dataseries Switzerland's Data Series in One Place | 0.2.0 | 0.2.0 |
datasets | 4.4.1 | 4.4.1 |
dataverse Client for Dataverse 4+ Repositories | 0.3.13 | 0.3.13 |
DataVisualizations Visualizations of High-Dimensional Data | 1.3.2 | 1.3.2 |
datawizard Easy Data Wrangling and Statistical Transformations | 0.9.1 | 0.9.1 |
date Functions for Handling Dates | 1.2-39 | 1.2-39 |
datetimeutils Utilities for Dates and Times | 0.6-3 | 0.6-3 |
Davies The Davies Quantile Function | 1.2-0 | 1.2-0 |
dbarts Discrete Bayesian Additive Regression Trees Sampler | 0.9-25 | 0.9-25 |
DBI R Database Interface | 1.2.1 | 1.2.1 |
DBItest Testing DBI Backends | 1.8.0 | 1.8.0 |
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 | 2.9-0 | 2.9-0 |
dbparser Drugs Databases Parser | 2.0.1 | 2.0.1 |
dbplyr A 'dplyr' Back End for Databases | 2.4.0 | 2.4.0 |
dbscan Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Related Algorithms | 1.1-12 | 1.1-12 |
dbx A Fast, Easy-to-Use Database Interface | 0.3.1 | 0.3.1 |
DChaos Chaotic Time Series Analysis | 0.1-7 | 0.1-7 |
dclone Data Cloning and MCMC Tools for Maximum Likelihood Methods | 2.3-0 | 2.3-0 |
DCluster Functions for the Detection of Spatial Clusters of Diseases | 0.2-9 | 0.2-9 |
DClusterm Model-Based Detection of Disease Clusters | 1.0-1 | 1.0-1 |
dcov A Fast Implementation of Distance Covariance | 0.1.1 | 0.1.1 |
dCovTS Distance Covariance and Correlation for Time Series Analysis | 1.4 | 1.4 |
dcurver Utility Functions for Davidian Curves | 0.9.2 | 0.9.2 |
ddalpha Depth-Based Classification and Calculation of Data Depth | 1.3.15 | 1.3.15 |
ddCt | 1.54.0 | 1.54.0 |
dde Solve Delay Differential Equations | 1.0.5 | 1.0.5 |
DDRTree Learning Principal Graphs with DDRTree | 0.1.5 | 0.1.5 |
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 | 1.0.0 | 1.0.0 |
decompr Global Value Chain Decomposition | 6.4.0 | 6.4.0 |
decor Retrieve Code Decorations | 1.0.1 | 1.0.1 |
deducorrect Deductive Correction, Deductive Imputation, and Deterministic Correction | 1.3.7 | 1.3.7 |
deductive Data Correction and Imputation Using Deductive Methods | 1.0.0 | 1.0.0 |
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 |
dejaVu Multiple Imputation for Recurrent Events | 0.3.0 | 0.3.0 |
Delaporte Statistical Functions for the Delaporte Distribution | 8.3.0 | 8.3.0 |
DelayedArray | 0.24.0 | 0.24.0 |
DelayedMatrixStats | 1.20.0 | 1.20.0 |
deldir Delaunay Triangulation and Dirichlet (Voronoi) Tessellation | 2.0-2 | 2.0-2 |
deltaPlotR Identification of Dichotomous Differential Item Functioning (DIF) using Angoff's Delta Plot Method | 1.6 | 1.6 |
dendextend Extending 'dendrogram' Functionality in R | 1.17.1 | 1.17.1 |
denoiseR Regularized Low Rank Matrix Estimation | 1.0.2 | 1.0.2 |
denseFLMM Functional Linear Mixed Models for Densely Sampled Data | 0.1.2 | 0.1.2 |
densEstBayes Density Estimation via Bayesian Inference Engines | 1.0-2.2 | 1.0-2.2 |
densityClust Clustering by Fast Search and Find of Density Peaks | 0.3 | 0.3 |
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 | 1.1-3 | 1.1-3 |
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 | 1.4.3 | 1.4.3 |
DescTools Tools for Descriptive Statistics | 0.99.53 | 0.99.53 |
DESeq2 | 1.38.2 | 1.38.2 |
designGG Computational tool for designing genetical genomics experiments. | 1.1 | 1.1 |
DesignLibrary Library of Research Designs | 0.1.10 | 0.1.10 |
designmatch Matched Samples that are Balanced and Representative by Design | 0.4.1 | 0.4.1 |
desirability Function Optimization and Ranking via Desirability Functions | 2.1 | 2.1 |
deSolve Solvers for Initial Value Problems of Differential Equations ('ODE', 'DAE', 'DDE') | 1.40 | 1.40 |
desplot Plotting Field Plans for Agricultural Experiments | 1.10 | 1.10 |
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 |
devEMF EMF Graphics Output Device | 4.4-1 | 4.4-1 |
devtools Tools to Make Developing R Packages Easier | 2.4.4 | 2.4.4 |
dexter Data Management and Analysis of Tests | 1.4.0 | 1.4.0 |
dextergui A Graphical User Interface for Dexter | 0.2.6 | 0.2.6 |
dexterMST CML and Bayesian Calibration of Multistage Tests | 0.9.6 | 0.9.6 |
dfcomb Phase I/II Adaptive Dose-Finding Design for Combination Studies | 3.1-1 | 3.1-1 |
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 |
dfmta Phase I/II Adaptive Dose-Finding Design for MTA | 1.7-3 | 1.7-3 |
dfoptim Derivative-Free Optimization | 2023.1.0 | 2023.1.0 |
dfped Extrapolation and Bridging of Adult Information in Early Phase Dose-Finding Paediatrics Studies | 1.1 | 1.1 |
dfpk Bayesian Dose-Finding Designs using Pharmacokinetics (PK) for Phase I Clinical Trials | 3.5.1 | 3.5.1 |
dggridR Discrete Global Grids | 3.0.0 | 3.0.0 |
dglm Double Generalized Linear Models | 1.8.4 | 1.8.4 |
dgumbel The Gumbel Distribution Functions and Gradients | 1.0.1 | 1.0.1 |
DHARMa Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models | 0.4.6 | 0.4.6 |
DHS.rates Calculates Demographic Indicators | 0.9.2 | 0.9.2 |
diagis Diagnostic Plot and Multivariate Summary Statistics of Weighted Samples from Importance Sampling | 0.2.3 | 0.2.3 |
diagmeta Meta-Analysis of Diagnostic Accuracy Studies with Several Cutpoints | 0.5-0 | 0.5-0 |
DiagnosisMed Diagnostic test accuracy evaluation for medical professionals. | 0.2.3 | 0.2.3 |
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 | 1.0.10 | 1.0.10 |
DiagrammeRsvg Export DiagrammeR Graphviz Graphs as SVG | 0.1 | 0.1 |
dials Tools for Creating Tuning Parameter Values | 1.2.0 | 1.2.0 |
DiceDesign Designs of Computer Experiments | 1.10 | 1.10 |
DiceEval Construction and Evaluation of Metamodels | 1.6.1 | 1.6.1 |
DiceKriging Kriging Methods for Computer Experiments | 1.6.0 | 1.6.0 |
DiceOptim Kriging-Based Optimization for Computer Experiments | 2.1.1 | 2.1.1 |
dichromat Color Schemes for Dichromats | 2.0-0.1 | 2.0-0.1 |
DICOMread Reading and Saving DICOM Image Files | 0.0.0.3 | 0.0.0.3 |
dictionar6 R6 Dictionary Interface | 0.1.3 | 0.1.3 |
did Treatment Effects with Multiple Periods and Groups | 2.1.1 | 2.1.1 |
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) | 2.0.0 | 2.0.0 |
diffobj Diffs for R Objects | 0.3.5 | 0.3.5 |
diffpriv Easy Differential Privacy | 0.4.2 | 0.4.2 |
diffusion Forecast the Diffusion of New Products | 0.2.7 | 0.2.7 |
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 | 1.4.2-1 | 1.4.2-1 |
DIFplus Multilevel Mantel-Haenszel Statistics for Differential Item Functioning Detection | 1.1 | 1.1 |
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 | 0.6.34 | 0.6.34 |
digitize Use Data from Published Plots in R | 0.0.4 | 0.0.4 |
dimensionsR Gathering Bibliographic Records from 'Digital Science Dimensions' Using 'DSL' API | 0.0.3 | 0.0.3 |
dimRed A Framework for Dimensionality Reduction | 0.2.6 | 0.2.6 |
dina Bayesian Estimation of DINA Model | 2.0.0 | 2.0.0 |
dipm Depth Importance in Precision Medicine (DIPM) Method | 1.9 | 1.9 |
DiPs Directional Penalties for Optimal Matching in Observational Studies | 0.6.4 | 0.6.4 |
dipsaus A Dipping Sauce for Data Analysis and Visualizations | 0.2.8 | 0.2.8 |
diptest Hartigan's Dip Test Statistic for Unimodality - Corrected | 0.77-0 | 0.77-0 |
Dire Linear Regressions with a Latent Outcome Variable | 2.2.0 | 2.2.0 |
DIRECT Bayesian Clustering of Multivariate Data Under the Dirichlet-Process Prior | 1.1.0 | 1.1.0 |
DirectEffects Estimating Controlled Direct Effects for Explaining Causal Findings | 0.2.1 | 0.2.1 |
Directional A Collection of Functions for Directional Data Analysis | 6.4 | 6.4 |
directlabels Direct Labels for Multicolor Plots | 2024.1.21 | 2024.1.21 |
dirichletprocess Build Dirichlet Process Objects for Bayesian Modelling | 0.4.2 | 0.4.2 |
dirmult Estimation in Dirichlet-Multinomial Distribution | 0.1.3-5 | 0.1.3-5 |
disaggR Two-Steps Benchmarks for Time Series Disaggregation | 1.0.5.1 | 1.0.5.1 |
discgolf Discourse API Client | 0.2.0 | 0.2.0 |
disclap Discrete Laplace Exponential Family | 1.5.1 | 1.5.1 |
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 |
disk.frame Larger-than-RAM Disk-Based Data Manipulation Framework | 0.8.3 | 0.8.3 |
dismo Species Distribution Modeling | 1.3-14 | 1.3-14 |
disordR Non-Ordered Vectors | 0.9-8.2 | 0.9-8.2 |
Distance Distance Sampling Detection Function and Abundance Estimation | 1.0.9 | 1.0.9 |
distances Tools for Distance Metrics | 0.1.10 | 0.1.10 |
DistatisR DiSTATIS Three Way Metric Multidimensional Scaling | 1.0.1 | 1.0.1 |
distcrete Discrete Distribution Approximations | 1.0.3 | 1.0.3 |
distfree.cr Distribution-Free Confidence Region | 1.5.1 | 1.5.1 |
distill 'R Markdown' Format for Scientific and Technical Writing | 1.6 | 1.6 |
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 | 2.9.3 | 2.9.3 |
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 | 2.8.2 | 2.8.2 |
distrEx Extensions of Package 'distr' | 2.9.2 | 2.9.2 |
distributional Vectorised Probability Distributions | 0.3.2 | 0.3.2 |
distributions3 Probability Distributions as S3 Objects | 0.2.1 | 0.2.1 |
distributionsrd Distribution Fitting and Evaluation | 0.0.6 | 0.0.6 |
DistributionUtils Distribution Utilities | 0.6-1 | 0.6-1 |
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' | 2.8.2 | 2.8.2 |
distrTeach Extensions of Package 'distr' for Teaching Stochastics/Statistics in Secondary School | 2.9.1 | 2.9.1 |
distrTEst Estimation and Testing Classes Based on Package 'distr' | 2.8.2 | 2.8.2 |
distTails A Collection of Full Defined Distribution Tails | 0.1.2 | 0.1.2 |
dittodb A Test Environment for Database Requests | 0.1.7 | 0.1.7 |
diveMove Dive Analysis and Calibration | 1.6.2 | 1.6.2 |
divest Get Images Out of DICOM Format Quickly | 0.10.3 | 0.10.3 |
divseg Calculate Diversity and Segregation Indices | 0.0.5 | 0.0.5 |
dLagM Time Series Regression Models with Distributed Lag Models | 1.1.13 | 1.1.13 |
dlm Bayesian and Likelihood Analysis of Dynamic Linear Models | 1.1-6 | 1.1-6 |
dlnm Distributed Lag Non-Linear Models | 2.4.7 | 2.4.7 |
dlookr Tools for Data Diagnosis, Exploration, Transformation | 0.6.2 | 0.6.2 |
dlstats Download Stats of R Packages | 0.1.7 | 0.1.7 |
dMod Dynamic Modeling and Parameter Estimation in ODE Models | 1.0.2 | 1.0.2 |
dmri.tracking DiST - Diffusion Direction Smoothing and Tracking | 0.1.0 | 0.1.0 |
dng Distributions and Gradients | 0.2.1 | 0.2.1 |
doBy Groupwise Statistics, LSmeans, Linear Estimates, Utilities | 4.6.20 | 4.6.20 |
docopt Command-Line Interface Specification Language | 0.7.1 | 0.7.1 |
docopulae Optimal Designs for Copula Models | 0.4.0 | 0.4.0 |
dodgr Distances on Directed Graphs | 0.2.14 | 0.2.14 |
DoE.base Full Factorials, Orthogonal Arrays and Base Utilities for DoE Packages | 1.2-4 | 1.2-4 |
DoE.MIParray Creation of Arrays by Mixed Integer Programming | 1.0-1 | 1.0-1 |
DoE.wrapper Wrapper Package for Design of Experiments Functionality | 0.12 | 0.12 |
doFuture Use Foreach to Parallelize via the Future Framework | 1.0.1 | 1.0.1 |
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 |
doRNG Generic Reproducible Parallel Backend for 'foreach' Loops | 1.8.6 | 1.8.6 |
DOSE | 3.28.0 | 3.28.0 |
dosearch Causal Effect Identification from Multiple Incomplete Data Sources | 1.0.8 | 1.0.8 |
DoseFinding Planning and Analyzing Dose Finding Experiments | 1.1-1 | 1.1-1 |
doSNOW Foreach Parallel Adaptor for the 'snow' Package | 1.0.20 | 1.0.20 |
DOSPortfolio Dynamic Optimal Shrinkage Portfolio | 0.1.0 | 0.1.0 |
dosresmeta Multivariate Dose-Response Meta-Analysis | 2.0.1 | 2.0.1 |
dotCall64 Enhanced Foreign Function Interface Supporting Long Vectors | 1.1-1 | 1.1-1 |
dotwhisker Dot-and-Whisker Plots of Regression Results | 0.7.4 | 0.7.4 |
DoubleML Double Machine Learning in R | 0.5.3 | 0.5.3 |
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 | 0.4.3 | 0.4.3 |
downloader Download Files over HTTP and HTTPS | 0.4 | 0.4 |
dparser Port of 'Dparser' Package | 1.3.1-11 | 1.3.1-11 |
dplyr A Grammar of Data Manipulation | 1.1.4 | 1.1.4 |
DPQ Density, Probability, Quantile ('DPQ') Computations | 0.5-8 | 0.5-8 |
dqrng Fast Pseudo Random Number Generators | 0.3.2 | 0.3.2 |
dr Methods for Dimension Reduction for Regression | 3.0.10 | 3.0.10 |
dr4pl Dose Response Data Analysis using the 4 Parameter Logistic (4pl) Model | 2.0.0 | 2.0.0 |
drake A Pipeline Toolkit for Reproducible Computation at Scale | 7.13.8 | 7.13.8 |
drc Analysis of Dose-Response Curves | 3.0-1 | 3.0-1 |
DRDID Doubly Robust Difference-in-Differences Estimators | 1.0.6 | 1.0.6 |
dreamerr Error Handling Made Easy | 1.4.0 | 1.4.0 |
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 |
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 |
drtmle Doubly-Robust Nonparametric Estimation and Inference | 1.1.1 | 1.1.1 |
dsa Seasonal Adjustment of Daily Time Series | 1.0.12 | 1.0.12 |
DSAIDE Dynamical Systems Approach to Infectious Disease Epidemiology (Ecology/Evolution) | 0.9.6 | 0.9.6 |
dse Dynamic Systems Estimation (Time Series Package) | 2020.2-1 | 2020.2-1 |
DSI 'DataSHIELD' Interface | 1.5.0 | 1.5.0 |
DSL Distributed Storage and List | 0.1-7 | 0.1-7 |
dslabs Data Science Labs | 0.7.4 | 0.7.4 |
dsm Density Surface Modelling of Distance Sampling Data | 2.3.3 | 2.3.3 |
dstat Conditional Sensitivity Analysis for Matched Observational Studies | 1.0.4 | 1.0.4 |
DT A Wrapper of the JavaScript Library 'DataTables' | 0.31 | 0.31 |
DTAplots Creates Plots Accompanying Bayesian Diagnostic Test Accuracy Meta-Analyses | 1.0.2.5 | 1.0.2.5 |
DTAT Dose Titration Algorithm Tuning | 0.3-6 | 0.3-6 |
DtD Distance to Default | 0.2.2 | 0.2.2 |
DTDA Doubly Truncated Data Analysis | 3.0.1 | 3.0.1 |
dti Analysis of Diffusion Weighted Imaging (DWI) Data | 1.5.4 | 1.5.4 |
dtplyr Data Table Back-End for 'dplyr' | 1.3.1 | 1.3.1 |
DTRlearn2 Statistical Learning Methods for Optimizing Dynamic Treatment Regimes | 1.1 | 1.1 |
DTRreg DTR Estimation and Inference via G-Estimation, Dynamic WOLS, Q-Learning, and Dynamic Weighted Survival Modeling (DWSurv) | 2.0 | 2.0 |
DTSg A Class for Working with Time Series Data Based on 'data.table' and 'R6' with Largely Optional Reference Semantics | 1.1.3 | 1.1.3 |
dtts 'data.table' Time-Series | 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 |
dual Automatic Differentiation with Dual Numbers | 0.0.5 | 0.0.5 |
duckduckr Simple Client for the DuckDuckGo Instant Answer API | 1.0.0 | 1.0.0 |
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 |
dynamicTreeCut Methods for Detection of Clusters in Hierarchical Clustering Dendrograms | 1.63-1 | 1.63-1 |
dynaTree Dynamic Trees for Learning and Design | 1.2-16 | 1.2-16 |
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 | 0.4-6 | 0.4-6 |
DynTxRegime Methods for Estimating Optimal Dynamic Treatment Regimes | 4.15 | 4.15 |
e1071 Misc Functions of the Department of Statistics, Probability Theory Group (Formerly: E1071), TU Wien | 1.7-14 | 1.7-14 |
eaf Plots of the Empirical Attainment Function | 2.3 | 2.3 |
earlyR Estimation of Transmissibility in the Early Stages of a Disease Outbreak | 0.0.5 | 0.0.5 |
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 |
easypower Sample Size Estimation for Experimental Designs | 1.0.1 | 1.0.1 |
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 |
ebal Entropy Reweighting to Create Balanced Samples | 0.1-8 | 0.1-8 |
EbayesThresh Empirical Bayes Thresholding and Related Methods | 1.4-12 | 1.4-12 |
ebdbNet Empirical Bayes Estimation of Dynamic Bayesian Networks | 1.2.8 | 1.2.8 |
EBMAforecast Estimate Ensemble Bayesian Model Averaging Forecasts using Gibbs Sampling or EM-Algorithms | 1.0.31 | 1.0.31 |
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 | 0.1.9 | 0.1.9 |
ECLRMC Ensemble Correlation-Based Low-Rank Matrix Completion | 1.0 | 1.0 |
ecm Build Error Correction Models | 7.0.0 | 7.0.0 |
eco Ecological Inference in 2x2 Tables | 4.0-1 | 4.0-1 |
ecodist Dissimilarity-Based Functions for Ecological Analysis | 2.1.3 | 2.1.3 |
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 | 0.2.4 | 0.2.4 |
ECOSolveR Embedded Conic Solver in R | 0.5.5 | 0.5.5 |
ecoval Procedures for Ecological Assessment of Surface Waters | 1.2.9 | 1.2.9 |
ecp Non-Parametric Multiple Change-Point Analysis of Multivariate Data | 3.1.5 | 3.1.5 |
ecr Evolutionary Computation in R | 2.1.1 | 2.1.1 |
Ecume Equality of 2 (or k) Continuous Univariate and Multivariate Distributions | 0.9.1 | 0.9.1 |
edfReader Reading EDF(+) and BDF(+) Files | 1.2.1 | 1.2.1 |
edgeR | 4.0.1 | 4.0.1 |
edina Bayesian Estimation of an Exploratory Deterministic Input, Noisy and Gate Model | 0.1.1 | 0.1.1 |
editrules Parsing, Applying, and Manipulating Data Cleaning Rules | 2.9.3 | 2.9.3 |
edmcr Euclidean Distance Matrix Completion Tools | 0.2.0 | 0.2.0 |
edmdata Data Sets for Psychometric Modeling | 1.2.0 | 1.2.0 |
edstan Stan Models for Item Response Theory | 1.0.6 | 1.0.6 |
EdSurvey Analysis of NCES Education Survey and Assessment Data | 4.0.4 | 4.0.4 |
eechidna Exploring Election and Census Highly Informative Data Nationally for Australia | 1.4.1 | 1.4.1 |
eefAnalytics Robust Analytical Methods for Evaluating Educational Interventions using Randomised Controlled Trials Designs | 1.1.1 | 1.1.1 |
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 | 2.1.3 | 2.1.3 |
EffectLiteR Average and Conditional Effects | 0.4-6 | 0.4-6 |
effects Effect Displays for Linear, Generalized Linear, and Other Models | 4.2-1 | 4.2-1 |
effectsize Indices of Effect Size | 0.8.6 | 0.8.6 |
EffectTreat Prediction of Therapeutic Success | 1.1 | 1.1 |
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 | 2.0.3 | 2.0.3 |
egcm Engle-Granger Cointegration Models | 1.0.13 | 1.0.13 |
egg Extensions for 'ggplot2': Custom Geom, Custom Themes, Plot Alignment, Labelled Panels, Symmetric Scales, and Fixed Panel Size | 0.4.5 | 0.4.5 |
egor Import and Analyse Ego-Centered Network Data | 1.23.3 | 1.23.3 |
EGRET Exploration and Graphics for RivEr Trends | 3.0.9 | 3.0.9 |
EGRETci Exploration and Graphics for RivEr Trends Confidence Intervals | 2.0.4 | 2.0.4 |
eha Event History Analysis | 2.11.2 | 2.11.2 |
ei Ecological Inference | 1.3-3 | 1.3-3 |
eicm Explicit Interaction Community Models | 1.0.3 | 1.0.3 |
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 |
elasdics Elastic Analysis of Sparse, Dense and Irregular Curves | 1.1.3 | 1.1.3 |
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 | 0.99.0 | 0.99.0 |
elfDistr Kumaraswamy Complementary Weibull Geometric (Kw-CWG) Probability Distribution | 1.0.0 | 1.0.0 |
ellipse Functions for Drawing Ellipses and Ellipse-Like Confidence Regions | 0.5.0 | 0.5.0 |
ellipsis Tools for Working with ... | 0.3.2 | 0.3.2 |
elliptic Weierstrass and Jacobi Elliptic Functions | 1.4-0 | 1.4-0 |
elmNN Implementation of ELM (Extreme Learning Machine ) algorithm for<U+000a>SLFN ( Single Hidden Layer Feedforward Neural Networks ) | 1.0 | 1.0 |
elo Ranking Teams by Elo Rating and Comparable Methods | 3.0.2 | 3.0.2 |
EloChoice Preference Rating for Visual Stimuli Based on Elo Ratings | 0.29.4 | 0.29.4 |
EloOptimized Optimized Elo Rating Method for Obtaining Dominance Ranks | 0.3.1 | 0.3.1 |
EloRating Animal Dominance Hierarchies by Elo Rating | 0.46.11 | 0.46.11 |
ELYP Empirical Likelihood Analysis for the Cox Model and Yang-Prentice (2005) Model | 0.7-5 | 0.7-5 |
emayili Send Email Messages | 0.7.18 | 0.7.18 |
EMbC Expectation-Maximization Binary Clustering | 2.0.4 | 2.0.4 |
EMCluster EM Algorithm for Model-Based Clustering of Finite Mixture Gaussian Distribution | 0.2-15 | 0.2-15 |
EMD Empirical Mode Decomposition and Hilbert Spectral Analysis | 1.5.9 | 1.5.9 |
emdbook Support Functions and Data for "Ecological Models and Data" | 1.3.13 | 1.3.13 |
emdi Estimating and Mapping Disaggregated Indicators | 2.2.1 | 2.2.1 |
emg Exponentially Modified Gaussian (EMG) Distribution | 1.0.9 | 1.0.9 |
emmeans Estimated Marginal Means, aka Least-Squares Means | 1.10.0 | 1.10.0 |
emoa Evolutionary Multiobjective Optimization Algorithms | 0.5-2 | 0.5-2 |
empichar Evaluates the Empirical Characteristic Function for Multivariate Samples | 1.0.0 | 1.0.0 |
EmpiricalCalibration Routines for Performing Empirical Calibration of Observational Study Estimates | 3.1.2 | 3.1.2 |
emplik Empirical Likelihood Ratio for Censored/Truncated Data | 1.3-1 | 1.3-1 |
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 |
endoSwitch Endogenous Switching Regression Models | 1.0.0 | 1.0.0 |
endtoend Transmissions and Receptions in an End to End Network | 2.29 | 2.29 |
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 |
EngrExpt Data sets from "Introductory Statistics for Engineering<U+000a>Experimentation" | 0.1-8 | 0.1-8 |
engsoccerdata English and European Soccer Results 1871-2016 | 0.1.5 | 0.1.5 |
enpls Ensemble Partial Least Squares Regression | 6.1 | 6.1 |
enrichplot | 1.22.0 | 1.22.0 |
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 | 2.22.0 | 2.22.0 |
ensembleBMA Probabilistic Forecasting using Ensembles and Bayesian Model Averaging | 5.1.8 | 5.1.8 |
entropy Estimation of Entropy, Mutual Information and Related Quantities | 1.3.1 | 1.3.1 |
EntropyMCMC MCMC Simulation and Convergence Evaluation using Entropy and Kullback-Leibler Divergence Estimation | 1.0.4 | 1.0.4 |
envnames Keep Track of User-Defined Environment Names | 0.4.1 | 0.4.1 |
EnvStats Package for Environmental Statistics, Including US EPA Guidance | 2.8.1 | 2.8.1 |
Epi Statistical Analysis in Epidemiology | 2.47.1 | 2.47.1 |
epibasix Elementary Epidemiological Functions for Epidemiology and Biostatistics | 1.5 | 1.5 |
epicalc Epidemiological calculator | 2.15.1.0 | 2.15.1.0 |
epicontacts Handling, Visualisation and Analysis of Epidemiological Contacts | 1.1.3 | 1.1.3 |
EpiContactTrace Epidemiological Tool for Contact Tracing | 0.17.0 | 0.17.0 |
EpiCurve Plot an Epidemic Curve | 2.4-2 | 2.4-2 |
epiDisplay Epidemiological Data Display Package | 3.5.0.2 | 3.5.0.2 |
EpiEstim Estimate Time Varying Reproduction Numbers from Epidemic Curves | 2.2-4 | 2.2-4 |
epiflows Predicting Disease Spread from Flow Data | 0.2.1 | 0.2.1 |
EpiILM Spatial and Network Based Individual Level Models for Epidemics | 1.5.2 | 1.5.2 |
EpiILMCT Continuous Time Distance-Based and Network-Based Individual Level Models for Epidemics | 1.1.7 | 1.1.7 |
epimdr Functions and Data for "Epidemics: Models and Data in R" | 0.6-5 | 0.6-5 |
EpiModel Mathematical Modeling of Infectious Disease Dynamics | 2.4.0 | 2.4.0 |
epinet Epidemic/Network-Related Tools | 2.1.11 | 2.1.11 |
epiR Tools for the Analysis of Epidemiological Data | 2.0.66 | 2.0.66 |
EpiReport Epidemiological Report | 1.0.2 | 1.0.2 |
episensr Basic Sensitivity Analysis of Epidemiological Results | 1.1.0 | 1.1.0 |
epitools Epidemiology Tools | 0.5-10.1 | 0.5-10.1 |
epitrix Small Helpers and Tricks for Epidemics Analysis | 0.4.0 | 0.4.0 |
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 |
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 | 4.6.0 | 4.6.0 |
ergm.count Fit, Simulate and Diagnose Exponential-Family Models for Networks with Count Edges | 4.1.1 | 4.1.1 |
ergm.ego Fit, Simulate and Diagnose Exponential-Family Random Graph Models to Egocentrically Sampled Network Data | 1.1.0 | 1.1.0 |
ergm.multi Fit, Simulate and Diagnose Exponential-Family Models for Multiple or Multilayer Networks | 0.2.0 | 0.2.0 |
eRm Extended Rasch Modeling | 1.0-4 | 1.0-4 |
errorlocate Locate Errors with Validation Rules | 1.1.1 | 1.1.1 |
errors Uncertainty Propagation for R Vectors | 0.4.1 | 0.4.1 |
errum Exploratory Reduced Reparameterized Unified Model Estimation | 0.0.3 | 0.0.3 |
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 |
esemifar Smoothing Long-Memory Time Series | 1.0.2 | 1.0.2 |
ESG A Package for Asset Projection | 1.3 | 1.3 |
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 |
EstimateGroupNetwork Perform the Joint Graphical Lasso and Selects Tuning Parameters | 0.3.1 | 0.3.1 |
estimatr Fast Estimators for Design-Based Inference | 1.0.2 | 1.0.2 |
estimraw Estimation of Four-Fold Table Cell Frequencies (Raw Data) from Effect Size Measures | 1.0.0 | 1.0.0 |
estmeansd Estimating the Sample Mean and Standard Deviation from Commonly Reported Quantiles in Meta-Analysis | 1.0.1 | 1.0.1 |
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 |
etrm Energy Trading and Risk Management | 1.0.1 | 1.0.1 |
etrunct Computes Moments of Univariate Truncated t Distribution | 0.1 | 0.1 |
EUfootball Football Match Data of European Leagues | 0.0.1 | 0.0.1 |
europepmc R Interface to the Europe PubMed Central RESTful Web Service | 0.4.3 | 0.4.3 |
eurostat Tools for Eurostat Open Data | 4.0.0 | 4.0.0 |
eva Extreme Value Analysis with Goodness-of-Fit Testing | 0.2.6 | 0.2.6 |
evalITR Evaluating Individualized Treatment Rules | 1.0.0 | 1.0.0 |
evaluate Parsing and Evaluation Tools that Provide More Details than the Default | 0.23 | 0.23 |
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 | 2.0.2 | 2.0.2 |
evclust Evidential Clustering | 2.0.3 | 2.0.3 |
evd Functions for Extreme Value Distributions | 2.3-6.1 | 2.3-6.1 |
evgam Generalised Additive Extreme Value Models | 1.0.0 | 1.0.0 |
EvidenceSynthesis Synthesizing Causal Evidence in a Distributed Research Network | 0.5.0 | 0.5.0 |
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 |
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 |
exactci Exact P-Values and Matching Confidence Intervals for Simple Discrete Parametric Cases | 1.4-4 | 1.4-4 |
exactextractr Fast Extraction from Raster Datasets using Polygons | 0.10.0 | 0.10.0 |
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 | 1.3.6 | 1.3.6 |
exdex Estimation of the Extremal Index | 1.2.3 | 1.2.3 |
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' | 0.999-9 | 0.999-9 |
export Streamlined Export of Graphs and Data Tables | 0.3.0 | 0.3.0 |
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 |
extraDistr Additional Univariate and Multivariate Distributions | 1.10.0 | 1.10.0 |
extrafont Tools for Using Fonts | 0.19 | 0.19 |
extrafontdb Package for holding the database for the extrafont package | 1.0 | 1.0 |
extraoperators Extra Binary Relational and Logical Operators | 0.3.0 | 0.3.0 |
extras Helper Functions for Bayesian Analyses | 0.6.1 | 0.6.1 |
extraTrees Extremely Randomized Trees (ExtraTrees) Method for<U+000a>Classification and Regression | 1.0.5 | 1.0.5 |
ExtremalDep Extremal Dependence Models | 0.0.4-1 | 0.0.4-1 |
ExtremeBounds Extreme Bounds Analysis (EBA) | 0.1.7 | 0.1.7 |
extremefit Estimation of Extreme Conditional Quantiles and Probabilities | 1.0.2 | 1.0.2 |
ExtremeRisks Extreme Risk Measures | 0.0.4 | 0.0.4 |
extRemes Extreme Value Analysis | 2.1-3 | 2.1-3 |
extremeStat Extreme Value Statistics and Quantile Estimation | 1.5.9 | 1.5.9 |
extremevalues Univariate Outlier Detection | 2.3.3 | 2.3.3 |
extremis Statistics of Extremes | 1.2.1 | 1.2.1 |
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 |
ez Easy Analysis and Visualization of Factorial Experiments | 4.4-0 | 4.4-0 |
fable Forecasting Models for Tidy Time Series | 0.3.3 | 0.3.3 |
fable.prophet Prophet Modelling Interface for 'fable' | 0.1.0 | 0.1.0 |
fabletools Core Tools for Packages in the 'fable' Framework | 0.3.4 | 0.3.4 |
fabricatr Imagine Your Data Before You Collect It | 1.0.0 | 1.0.0 |
face Fast Covariance Estimation for Sparse Functional Data | 0.1-6 | 0.1-6 |
FactoClass Combination of Factorial Methods and Cluster Analysis | 1.2.8 | 1.2.8 |
factoextra Extract and Visualize the Results of Multivariate Data Analyses | 1.0.7 | 1.0.7 |
FactoMineR Multivariate Exploratory Data Analysis and Data Mining | 2.9 | 2.9 |
factorstochvol Bayesian Estimation of (Sparse) Latent Factor Stochastic Volatility Models | 1.1.0 | 1.1.0 |
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 | 1.0.6 | 1.0.6 |
FAOSTAT Download Data from the FAOSTAT Database | 2.3.0 | 2.3.0 |
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 | 4023.85 | 4023.85 |
fasstr Analyze, Summarize, and Visualize Daily Streamflow Data | 0.5.1 | 0.5.1 |
fastcluster Fast Hierarchical Clustering Routines for R and 'Python' | 1.2.6 | 1.2.6 |
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 | 1.7.3 | 1.7.3 |
fastGHQuad Fast 'Rcpp' Implementation of Gauss-Hermite Quadrature | 1.0.1 | 1.0.1 |
fastICA FastICA Algorithms to Perform ICA and Projection Pursuit | 1.2-4 | 1.2-4 |
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 | 1.1-4 | 1.1-4 |
fastpseudo Fast Pseudo Observations | 0.1 | 0.1 |
fastRhockey Functions to Access Premier Hockey Federation and National Hockey League Play by Play Data | 0.4.0 | 0.4.0 |
fastrmodels Models for the 'nflfastR' Package | 1.0.2 | 1.0.2 |
FastRWeb Fast Interactive Framework for Web Scripting Using R | 1.2-1 | 1.2-1 |
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 | 0.2.2 | 0.2.2 |
FatTailsR Kiener Distributions and Fat Tails in Finance | 1.8-0 | 1.8-0 |
fauxpas HTTP Error Helpers | 0.5.2 | 0.5.2 |
FAVAR Bayesian Analysis of a FAVAR Model | 0.1.3 | 0.1.3 |
fBasics Rmetrics - Markets and Basic Statistics | 4032.96 | 4032.96 |
FBFsearch Algorithm for Searching the Space of Gaussian Directed Acyclic Graph Models Through Moment Fractional Bayes Factors | 1.2 | 1.2 |
fBonds Rmetrics - Pricing and Evaluating Bonds | 3042.78 | 3042.78 |
fbRads Analyzing and Managing Facebook Ads from R | 17.0.0 | 17.0.0 |
fbRanks Association Football (Soccer) Ranking via Poisson Regression | 2.0 | 2.0 |
fclust Fuzzy Clustering | 2.1.1.1 | 2.1.1.1 |
fCopulae Rmetrics - Bivariate Dependence Structures with Copulae | 4022.85 | 4022.85 |
FCPS Fundamental Clustering Problems Suite | 1.3.4 | 1.3.4 |
FD Measuring Functional Diversity (FD) from Multiple Traits, and Other Tools for Functional Ecology | 1.0-12.2 | 1.0-12.2 |
fda Functional Data Analysis | 6.1.4 | 6.1.4 |
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 |
fdANOVA Analysis of Variance for Univariate and Multivariate Functional Data | 0.1.2 | 0.1.2 |
fdaoutlier Outlier Detection Tools for Functional Data Analysis | 0.2.1 | 0.2.1 |
fdapace Functional Data Analysis and Empirical Dynamics | 0.5.9 | 0.5.9 |
fdaPDE Physics-Informed Spatial and Functional Data Analysis | 1.1-17 | 1.1-17 |
fdasrvf Elastic Functional Data Analysis | 2.1.0 | 2.1.0 |
fdatest Interval Testing Procedure for Functional Data | 2.1.1 | 2.1.1 |
FDboost Boosting Functional Regression Models | 1.1-2 | 1.1-2 |
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 | 0.3.1 | 0.3.1 |
feather R Bindings to the Feather 'API' | 0.3.5 | 0.3.5 |
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 | 4.0.0 | 4.0.0 |
FeedbackTS Analysis of Feedback in Time Series | 1.5 | 1.5 |
feisr Estimating Fixed Effects Individual Slope Models | 1.3.0 | 1.3.0 |
fExoticOptions Rmetrics - Pricing and Evaluating Exotic Option | 3042.80 | 3042.80 |
fExtremes Rmetrics - Modelling Extreme Events in Finance | 4032.84 | 4032.84 |
ff Memory-Efficient Storage of Large Data on Disk and Fast Access Functions | 4.0.12 | 4.0.12 |
FFD Freedom from Disease | 1.0-9 | 1.0-9 |
FFdownload Download Data from Kenneth French's Website | 1.1.0 | 1.1.0 |
FField Force field simulation for a set of points | 0.1.0 | 0.1.0 |
fflr Retrieve ESPN Fantasy Football Data | 2.2.1 | 2.2.1 |
ffscrapr API Client for Fantasy Football League Platforms | 1.4.8 | 1.4.8 |
ffsimulator Simulate Fantasy Football Seasons | 1.2.3 | 1.2.3 |
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 | 4031.90 | 4031.90 |
fgsea | 1.28.0 | 1.28.0 |
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 | ||
fields Tools for Spatial Data | 15.2 | 15.2 |
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 |
filearray File-Backed Array for Out-of-Memory Computation | 0.1.6 | 0.1.6 |
filehash Simple Key-Value Database | 2.4-5 | 2.4-5 |
filehashSQLite Simple Key-Value Database Using SQLite | 0.2-6 | 0.2-6 |
filelock Portable File Locking | 1.0.3 | 1.0.3 |
filematrix File-Backed Matrix Class with Convenient Read and Write Access | 1.3 | 1.3 |
FILEST Fine-Level Structure Simulator | 1.1.2 | 1.1.2 |
filling Matrix Completion, Imputation, and Inpainting Methods | 0.2.3 | 0.2.3 |
fImport Rmetrics - Importing Economic and Financial Data | 4021.86 | 4021.86 |
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 |
FindIt Finding Heterogeneous Treatment Effects | 1.2.0 | 1.2.0 |
findpython Functions to Find an Acceptable Python Binary | 1.0.7 | 1.0.7 |
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 | 0.4-9 | 0.4-9 |
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 |
fitbitScraper Scrapes Data from Fitbit | 0.1.8 | 0.1.8 |
fitcoach Personalized Coach for Fitbit and R API | 1.0 | 1.0 |
fitdistrplus Help to Fit of a Parametric Distribution to Non-Censored or Censored Data | 1.1-11 | 1.1-11 |
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 |
fitzRoy Easily Scrape and Process AFL Data | 1.3.0 | 1.3.0 |
FixedPoint Algorithms for Finding Fixed Point Vectors of Functions | 0.6.3 | 0.6.3 |
fixest Fast Fixed-Effects Estimations | 0.11.2 | 0.11.2 |
FKF Fast Kalman Filter | 0.2.5 | 0.2.5 |
FKF.SP Fast Kalman Filtering Through Sequential Processing | 0.3.1 | 0.3.1 |
flacco Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems | 1.8 | 1.8 |
FLAME Interpretable Matching for Causal Inference | 2.1.1 | 2.1.1 |
flare Family of Lasso Regression | 1.7.0.1 | 1.7.0.1 |
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 |
flexiblas 'FlexiBLAS' API Interface | 3.4.0 | 3.4.0 |
flexmix Flexible Mixture Modeling | 2.3-19 | 2.3-19 |
flexrsurv Flexible Relative Survival Analysis | 2.0.17 | 2.0.17 |
FlexScan Flexible Scan Statistics | 0.2.2 | 0.2.2 |
flexsurv Flexible Parametric Survival and Multi-State Models | 2.2.2 | 2.2.2 |
flextable Functions for Tabular Reporting | 0.9.4 | 0.9.4 |
float 32-Bit Floats | 0.3-2 | 0.3-2 |
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 | 1.5.4 | 1.5.4 |
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 |
FMC Factorial Experiments with Minimum Level Changes | 1.0.1 | 1.0.1 |
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 | 1.3.6.3 | 1.3.6.3 |
fmri Analysis of fMRI Experiments | 1.9.12 | 1.9.12 |
FMStable Finite Moment Stable Distributions | 0.1-4 | 0.1-4 |
fMultivar Rmetrics - Modeling of Multivariate Financial Return Distributions | 4031.84 | 4031.84 |
FNN Fast Nearest Neighbor Search Algorithms and Applications | 1.1.4 | 1.1.4 |
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 | 0.7-6 | 0.7-6 |
fontawesome Easily Work with 'Font Awesome' Icons | 0.5.2 | 0.5.2 |
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 |
footballpenaltiesBL Penalties in the German Men's Football Bundesliga | 1.0.0 | 1.0.0 |
footBayes Fitting Bayesian and MLE Football Models | 0.2.0 | 0.2.0 |
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 | 8.21.1 | 8.21.1 |
ForecastComb Forecast Combination Methods | 1.3.1 | 1.3.1 |
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 |
FoReco Forecast Reconciliation | 0.2.6 | 0.2.6 |
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', ... | 0.8-86 | 0.8-86 |
ForestFit Statistical Modelling for Plant Size Distributions | 2.2.3 | 2.2.3 |
forestmodel Forest Plots from Regression Models | 0.6.2 | 0.6.2 |
forestplot Advanced Forest Plot Using 'grid' Graphics | 3.1.3 | 3.1.3 |
forestploter Create Flexible Forest Plot | 1.1.1 | 1.1.1 |
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 |
forplo Flexible Forest Plots | 0.2.5 | 0.2.5 |
forward Robust Analysis using Forward Search | 1.0.6 | 1.0.6 |
foster Forest Structure Extrapolation with R | 0.1.1 | 0.1.1 |
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 | 2.2-10 | 2.2-10 |
fpcb Predictive Confidence Bands for Functional Time Series Forecasting | 0.1.0 | 0.1.0 |
fpCompare Reliable Comparison of Floating Point Numbers | 0.2.4 | 0.2.4 |
FPLdata Read in Fantasy Premier League Data | 0.1.0 | 0.1.0 |
fPortfolio Rmetrics - Portfolio Selection and Optimization | 4023.84 | 4023.84 |
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 |
frailtyEM Fitting Frailty Models with the EM Algorithm | 1.0.1 | 1.0.1 |
frailtyHL Frailty Models via Hierarchical Likelihood | 2.3 | 2.3 |
frailtypack Shared, Joint (Generalized) Frailty Models; Surrogate Endpoints | 3.5.1 | 3.5.1 |
frailtySurv General Semiparametric Shared Frailty Model | 1.3.8 | 1.3.8 |
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 |
frechet Statistical Analysis for Random Objects and Non-Euclidean Data | 0.3.0 | 0.3.0 |
fredr An R Client for the 'FRED' API | 2.1.0 | 2.1.0 |
freealg The Free Algebra | 1.1-1 | 1.1-1 |
freegroup The Free Group | 1.1-8 | 1.1-8 |
freesurferformats Read and Write 'FreeSurfer' Neuroimaging File Formats | 0.1.17 | 0.1.17 |
freetypeharfbuzz Deterministic Computation of Text Box Metrics | 0.2.6 | 0.2.6 |
fRegression Rmetrics - Regression Based Decision and Prediction | 4021.83 | 4021.83 |
frenchdata Download Data Sets from Kenneth's French Finance Data Library Site | 0.2.0 | 0.2.0 |
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 |
fresh Create Custom 'Bootstrap' Themes to Use in 'Shiny' | 0.2.0 | 0.2.0 |
FrF2 Fractional Factorial Designs with 2-Level Factors | 2.3-3 | 2.3-3 |
FrF2.catlg128 Catalogues of Resolution IV 128 Run 2-Level Fractional Factorials Up to 33 Factors that Do Have 5-Letter Words | 1.2-3 | 1.2-3 |
FRK Fixed Rank Kriging | 2.2.1 | 2.2.1 |
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' | 1.6.3 | 1.6.3 |
FSelector Selecting Attributes | 0.34 | 0.34 |
fsMTS Feature Selection for Multivariate Time Series | 0.1.7 | 0.1.7 |
FSMUMI Imputation of Time Series Based on Fuzzy Logic | 1.0 | 1.0 |
fsn Rosenthal's Fail Safe Number and Related Functions | 0.2 | 0.2 |
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 | 0.9.18 | 0.9.18 |
fTrading Rmetrics - Trading and Rebalancing Financial Instruments | 3042.79 | 3042.79 |
fts R Interface to 'tslib' (a Time Series Library in C++) | 0.9.9.2 | 0.9.9.2 |
ftsa Functional Time Series Analysis | 6.3 | 6.3 |
ftsspec Spectral Density Estimation and Comparison for Functional Time Series | 1.0.0 | 1.0.0 |
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 |
fUnitRoots Rmetrics - Modelling Trends and Unit Roots | 3042.79 | 3042.79 |
funLBM Model-Based Co-Clustering of Functional Data | 2.3 | 2.3 |
funtimes Functions for Time Series Analysis | 9.1 | 9.1 |
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 | 1.33.1 | 1.33.1 |
future.apply Apply Function to Elements in Parallel using Futures | 1.11.1 | 1.11.1 |
future.batchtools A Future API for Parallel and Distributed Processing using 'batchtools' | 0.12.1 | 0.12.1 |
fuzzyjoin Join Tables Together on Inexact Matching | 0.1.6 | 0.1.6 |
FuzzyNumbers Tools to Deal with Fuzzy Numbers | 0.4-7 | 0.4-7 |
FuzzyNumbers.Ext.2 Apply Two Fuzzy Numbers on a Monotone Function | 3.2 | 3.2 |
FuzzyR Fuzzy Logic Toolkit for R | 2.3.2 | 2.3.2 |
fwildclusterboot Fast Wild Cluster Bootstrap Inference for Linear Models | 0.13.0 | 0.13.0 |
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 |
GAD GAD: Analysis of variance from general principles | 1.1.1 | 1.1.1 |
gafit Genetic Algorithm for Curve Fitting | 0.5.1 | 0.5.1 |
gam Generalized Additive Models | 1.22-3 | 1.22-3 |
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 |
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 | 1.13-8 | 1.13-8 |
gamlss Generalised Additive Models for Location Scale and Shape | 5.4-20 | 5.4-20 |
gamlss.cens Fitting an Interval Response Variable Using `gamlss.family' Distributions | 5.0-7 | 5.0-7 |
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 | 6.1-1 | 6.1-1 |
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 | 1.5-3 | 1.5-3 |
gap.datasets Datasets for 'gap' | 0.0.6 | 0.0.6 |
gapfill Fill Missing Values in Satellite Data | 0.9.6-1 | 0.9.6-1 |
GARCHSK Estimating a GARCHSK Model and GJRSK Model | 0.1.0 | 0.1.0 |
garchx Flexible and Robust GARCH-X Modelling | 1.5 | 1.5 |
gargle Utilities for Working with Google APIs | 1.5.1 | 1.5.1 |
garma Fitting and Forecasting Gegenbauer ARMA Time Series Models | 0.9.13 | 0.9.13 |
GAS Generalized Autoregressive Score Models | 0.3.4 | 0.3.4 |
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 | 2.1.9 | 2.1.9 |
gbRd Utilities for processing Rd objects and files | 0.4-11 | 0.4-11 |
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 | 2.70.0 | 2.70.0 |
gdalUtilities Wrappers for 'GDAL' Utilities Executables | 1.2.5 | 1.2.5 |
gdata Various R Programming Tools for Data Manipulation | 3.0.0 | 3.0.0 |
GDINA The Generalized DINA Model Framework | 2.9.4 | 2.9.4 |
gdistance Distances and Routes on Geographical Grids | 1.6.4 | 1.6.4 |
gdpc Generalized Dynamic Principal Components | 1.1.2 | 1.1.2 |
gdtools Utilities for Graphical Rendering and Fonts Management | 0.3.5 | 0.3.5 |
gear Geostatistical Analysis in R | 0.3.4 | 0.3.4 |
gee Generalized Estimation Equation Solver | 4.13-26 | 4.13-26 |
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 | 2.0.11 | 2.0.11 |
gemtc Network Meta-Analysis Using Bayesian Methods | 1.0-2 | 1.0-2 |
GenABEL genome-wide SNP association analysis | 1.8-0 | 1.8-0 |
GenABEL.data Package contains data which is used by GenABEL example and test<U+000a>functions | 1.0.0 | 1.0.0 |
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 | 1.84.0 | 1.84.0 |
GeneNet Modeling and Inferring Gene Networks | 1.2.16 | 1.2.16 |
geneplotter | 1.76.0 | 1.76.0 |
generalCorr Generalized Correlations, Causal Paths and Portfolio Selection | 1.2.6 | 1.2.6 |
GeneralizedHyperbolic The Generalized Hyperbolic Distribution | 0.8-6 | 0.8-6 |
GeneralizedUmatrix Credible Visualization for Two-Dimensional Projections of Data | 1.2.6 | 1.2.6 |
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 |
genie Fast, Robust, and Outlier Resistant Hierarchical Clustering | 1.0.5 | 1.0.5 |
genieclust Fast and Robust Hierarchical Clustering with Noise Points Detection | 1.1.5-2 | 1.1.5-2 |
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 | 1.38.1 | 1.38.1 |
GenomeInfoDbData | 1.2.11 | 1.2.11 |
GenomicAlignments | 1.34.0 | 1.34.0 |
GenomicFeatures | 1.50.3 | 1.50.3 |
GenomicRanges | 1.54.1 | 1.54.1 |
genoPlotR Plot Publication-Grade Gene and Genome Maps | 0.8.11 | 0.8.11 |
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 | 1.1.14 | 1.1.14 |
genSurv Generating Multi-State Survival Data | 1.0.4 | 1.0.4 |
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 | 0.1.2 | 0.1.2 |
geojson Classes for 'GeoJSON' | 0.3.5 | 0.3.5 |
geojsonio Convert Data from and to 'GeoJSON' or 'TopoJSON' | 0.11.3 | 0.11.3 |
geojsonlint Tools for Validating 'GeoJSON' | 0.4.0 | 0.4.0 |
geojsonsf GeoJSON to Simple Feature Converter | 2.0.3 | 2.0.3 |
geoknife Web-Processing of Large Gridded Datasets | 1.6.10 | 1.6.10 |
GEOmap Topographic and Geologic Mapping | 2.5-5 | 2.5-5 |
geomapdata Data for Topographic and Geologic Mapping | 2.0-2 | 2.0-2 |
geometa Tools for Reading and Writing ISO/OGC Geographic Metadata | 0.7-1 | 0.7-1 |
GEOmetadb | ||
geometries Convert Between R Objects and Geometric Structures | 0.2.4 | 0.2.4 |
geometry Mesh Generation and Surface Tessellation | 0.4.7 | 0.4.7 |
geomorph Geometric Morphometric Analyses of 2D and 3D Landmark Data | 4.0.6 | 4.0.6 |
geonames Interface to the "Geonames" Spatial Query Web Service | 0.999 | 0.999 |
geonapi 'GeoNetwork' API R Interface | 0.7 | 0.7 |
GEOquery | 2.70.0 | 2.70.0 |
geos Open Source Geometry Engine ('GEOS') R API | 0.2.2 | 0.2.2 |
geosapi GeoServer REST API R Interface | 0.6-7 | 0.6-7 |
geosphere Spherical Trigonometry | 1.5-18 | 1.5-18 |
geospt Geostatistical Analysis and Design of Optimal Spatial Sampling Networks | 1.0-3 | 1.0-3 |
geotopbricks An R Plug-in for the Distributed Hydrological Model GEOtop | 1.5.8.0 | 1.5.8.0 |
geouy Geographic Information of Uruguay | 0.2.8 | 0.2.8 |
gert Simple Git Client for R | 2.0.1 | 2.0.1 |
getmstatistic Quantifying Systematic Heterogeneity in Meta-Analysis | 0.2.2 | 0.2.2 |
getopt C-Like 'getopt' Behavior | 1.20.4 | 1.20.4 |
GetoptLong Parsing Command-Line Arguments and Simple Variable Interpolation | 1.0.5 | 1.0.5 |
getPass Masked User Input | 0.2-4 | 0.2-4 |
gets General-to-Specific (GETS) Modelling and Indicator Saturation Methods | 0.37 | 0.37 |
getspres SPRE Statistics for Exploring Heterogeneity in Meta-Analysis | 0.2.0 | 0.2.0 |
GetTDData Get Data for Brazilian Bonds (Tesouro Direto) | 1.5.4 | 1.5.4 |
gfonts Offline 'Google' Fonts for 'Markdown' and 'Shiny' | 0.2.0 | 0.2.0 |
gfoRmula Parametric G-Formula | 1.0.3 | 1.0.3 |
ggalluvial Alluvial Plots in 'ggplot2' | 0.12.5 | 0.12.5 |
GGally Extension to 'ggplot2' | 2.2.0 | 2.2.0 |
ggalt Extra Coordinate Systems, 'Geoms', Statistical Transformations, Scales and Fonts for 'ggplot2' | 0.4.0 | 0.4.0 |
ggamma Generalized Gamma Probability Distribution | 1.0.1 | 1.0.1 |
gganimate A Grammar of Animated Graphics | 1.0.8 | 1.0.8 |
ggbeeswarm Categorical Scatter (Violin Point) Plots | 0.7.2 | 0.7.2 |
ggdag Analyze and Create Elegant Directed Acyclic Graphs | 0.2.12 | 0.2.12 |
ggdemetra 'ggplot2' Extension for Seasonal and Trading Day Adjustment with 'RJDemetra' | 0.2.7 | 0.2.7 |
ggdendro Create Dendrograms and Tree Diagrams Using 'ggplot2' | 0.1.23 | 0.1.23 |
ggdist Visualizations of Distributions and Uncertainty | 3.3.1 | 3.3.1 |
ggeffects Create Tidy Data Frames of Marginal Effects for 'ggplot' from Model Outputs | 1.3.4 | 1.3.4 |
ggExtra Add Marginal Histograms to 'ggplot2', and More 'ggplot2' Enhancements | 0.10.1 | 0.10.1 |
ggfittext Fit Text Inside a Box in 'ggplot2' | 0.10.2 | 0.10.2 |
ggforce Accelerating 'ggplot2' | 0.4.1 | 0.4.1 |
ggformula Formula Interface to the Grammar of Graphics | 0.12.0 | 0.12.0 |
ggfortify Data Visualization Tools for Statistical Analysis Results | 0.4.16 | 0.4.16 |
ggfun Miscellaneous Functions for 'ggplot2' | 0.1.4 | 0.1.4 |
gghalves Compose Half-Half Plots Using Your Favourite Geoms | 0.1.4 | 0.1.4 |
ggimage Use Image in 'ggplot2' | 0.3.3 | 0.3.3 |
GGIR Raw Accelerometer Data Analysis | 3.0-3 | 3.0-3 |
ggiraph Make 'ggplot2' Graphics Interactive | 0.8.2 | 0.8.2 |
ggm Graphical Markov Models with Mixed Graphs | ||
ggmap Spatial Visualization with ggplot2 | 4.0.0 | 4.0.0 |
ggmcmc Tools for Analyzing MCMC Simulations from Bayesian Inference | 1.5.1.1 | 1.5.1.1 |
ggnetwork Geometries to Plot Networks with 'ggplot2' | 0.5.12 | 0.5.12 |
ggnewscale Multiple Fill and Colour Scales in 'ggplot2' | 0.4.9 | 0.4.9 |
ggpath Robust Image Rendering Support for 'ggplot2' | 1.0.1 | 1.0.1 |
ggplot.multistats Multiple Summary Statistics for Binned Stats/Geometries | 1.0.0 | 1.0.0 |
ggplot2 Create Elegant Data Visualisations Using the Grammar of Graphics | 3.4.4 | 3.4.4 |
ggplot2movies Movies Data | 0.0.1 | 0.0.1 |
ggplotify Convert Plot to 'grob' or 'ggplot' Object | 0.1.2 | 0.1.2 |
ggpmisc Miscellaneous Extensions to 'ggplot2' | 0.5.5 | 0.5.5 |
ggpp Grammar Extensions to 'ggplot2' | 0.5.6 | 0.5.6 |
ggpubr 'ggplot2' Based Publication Ready Plots | 0.6.0 | 0.6.0 |
ggquiver Quiver Plots for 'ggplot2' | 0.3.3 | 0.3.3 |
ggraph An Implementation of Grammar of Graphics for Graphs and Networks | 2.0.6 | 2.0.6 |
ggrastr Rasterize Layers for 'ggplot2' | 1.0.1 | 1.0.1 |
ggrepel Automatically Position Non-Overlapping Text Labels with 'ggplot2' | 0.9.5 | 0.9.5 |
ggridges Ridgeline Plots in 'ggplot2' | 0.5.6 | 0.5.6 |
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 |
ggseqlogo A 'ggplot2' Extension for Drawing Publication-Ready Sequence Logos | 0.1 | 0.1 |
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 |
ggsoccer Plot Soccer Event Data | 0.1.7 | 0.1.7 |
ggspatial Spatial Data Framework for ggplot2 | 1.1.9 | 1.1.9 |
ggspectra Extensions to 'ggplot2' for Radiation Spectra | 0.3.12 | 0.3.12 |
ggstance Horizontal 'ggplot2' Components | ||
ggstats Extension to 'ggplot2' for Plotting Stats | 0.5.1 | 0.5.1 |
ggtext Improved Text Rendering Support for 'ggplot2' | 0.1.2 | 0.1.2 |
ggthemes Extra Themes, Scales and Geoms for 'ggplot2' | 5.0.0 | 5.0.0 |
ggtree | 3.10.0 | 3.10.0 |
ggvis Interactive Grammar of Graphics | 0.4.8 | 0.4.8 |
ggvoronoi Voronoi Diagrams and Heatmaps with 'ggplot2' | 0.8.5 | 0.8.5 |
gh 'GitHub' 'API' | 1.4.0 | 1.4.0 |
ghyp Generalized Hyperbolic Distribution and Its Special Cases | 1.6.4 | 1.6.4 |
Gifi Multivariate Analysis with Optimal Scaling | 0.4-0 | 0.4-0 |
gifski Highest Quality GIF Encoder | 1.12.0-2 | 1.12.0-2 |
gifti Reads in 'Neuroimaging' 'GIFTI' Files with Geometry Information | 0.8.0 | 0.8.0 |
GIGrvg Random Variate Generator for the GIG Distribution | 0.8 | 0.8 |
GillespieSSA Gillespie's Stochastic Simulation Algorithm (SSA) | 0.6.2 | 0.6.2 |
gimme Group Iterative Multiple Model Estimation | 0.7-15 | 0.7-15 |
giscoR Download Map Data from GISCO API - Eurostat | 0.4.0 | 0.4.0 |
gistr Work with 'GitHub' 'Gists' | 0.9.0 | 0.9.0 |
git2r Provides Access to Git Repositories | 0.33.0 | 0.33.0 |
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 | 0.2-6.5 | 0.2-6.5 |
gk g-and-k and g-and-h Distribution Functions | 0.6.0 | 0.6.0 |
glarma Generalized Linear Autoregressive Moving Average Models | 1.6-0 | 1.6-0 |
GlarmaVarSel Variable Selection in Sparse GLARMA Models | 1.0 | 1.0 |
glasso Graphical Lasso: Estimation of Gaussian Graphical Models | 1.11 | 1.11 |
glassoFast Fast Graphical LASSO | 1.0.1 | 1.0.1 |
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 | 2.0.0.9.3 | 2.0.0.9.3 |
glinternet Learning Interactions via Hierarchical Group-Lasso Regularization | 1.0.12 | 1.0.12 |
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 | 1.1.6 | 1.1.6 |
GLMMRR Generalized Linear Mixed Model (GLMM) for Binary Randomized Response Data | 0.5.0 | 0.5.0 |
glmnet Lasso and Elastic-Net Regularized Generalized Linear Models | 4.1-8 | 4.1-8 |
glmpath L1 Regularization Path for Generalized Linear Models and Cox Proportional Hazards Model | 0.98 | 0.98 |
glmx Generalized Linear Models Extended | 0.2-0 | 0.2-0 |
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 |
glue Interpreted String Literals | 1.7.0 | 1.7.0 |
gma Granger Mediation Analysis | 1.0 | 1.0 |
gmailr Access the 'Gmail' 'RESTful' API | 2.0.0 | 2.0.0 |
gmaps Wrapper and auxilliary functions for maps package to work with grid graphics system. | 0.2 | 0.2 |
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 |
gmeta Meta-Analysis via a Unified Framework of Confidence Distribution | 2.3-1 | 2.3-1 |
gmm Generalized Method of Moments and Generalized Empirical Likelihood | 1.8 | 1.8 |
GMMBoost Likelihood-Based Boosting for Generalized Mixed Models | 1.1.5 | 1.1.5 |
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 | 0.7-2 | 0.7-2 |
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 | 2.1.0 | 2.1.0 |
GNAR Methods for Fitting Network Time Series Models | 1.1.3 | 1.1.3 |
gnm Generalized Nonlinear Models | 1.1-5 | 1.1-5 |
gnorm Generalized Normal/Exponential Power Distribution | 1.0.0 | 1.0.0 |
GO.db | 3.18.0 | 3.18.0 |
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 | 2.0.1 | 2.0.1 |
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 | 2.1.1 | 2.1.1 |
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 | 0.8.4 | 0.8.4 |
googlesheets4 Access Google Sheets using the Sheets API V4 | 1.1.1 | 1.1.1 |
googleVis R Interface to Google Charts | 0.7.1 | 0.7.1 |
googleway Accesses Google Maps APIs to Retrieve Data and Plot Maps | 2.7.8 | 2.7.8 |
GOplot Visualization of Functional Analysis Data | 1.0.2 | 1.0.2 |
GORCure Fit Generalized Odds Rate Mixture Cure Model with Interval Censored Data | 2.0 | 2.0 |
GOSemSim | 2.28.0 | 2.28.0 |
gower Gower's Distance | 1.0.0 | 1.0.0 |
GPareto Gaussian Processes for Pareto Front Estimation and Optimization | 1.1.8 | 1.1.8 |
GPArotation Gradient Projection Factor Rotation | 2023.11-1 | 2023.11-1 |
GPCMlasso Differential Item Functioning in Generalized Partial Credit Models | 0.1-6 | 0.1-6 |
GPFDA Gaussian Process for Functional Data Analysis | 3.1.3 | 3.1.3 |
GPfit Gaussian Processes Modeling | 1.0-8 | 1.0-8 |
gplots Various R Programming Tools for Plotting Data | 3.1.3 | 3.1.3 |
gprofiler2 Interface to the 'g:Profiler' Toolset | 0.2.2 | 0.2.2 |
GramQuad Gram Quadrature | 0.1.1 | 0.1.1 |
granova Graphical Analysis of Variance | 2.1 | 2.1 |
graph graph: A package to handle graph data structures | ||
graphicalExtremes Statistical Methodology for Graphical Extreme Value Models | 0.3.0 | 0.3.0 |
graphicalVAR Graphical VAR for Experience Sampling Data | 0.3.3 | 0.3.3 |
graphics | 4.4.1 | 4.4.1 |
graphlayouts Additional Layout Algorithms for Network Visualizations | 1.1.0 | 1.1.0 |
graphTweets Visualise Twitter Interactions | 0.5.3 | 0.5.3 |
grates Grouped Date Classes | 1.1.0 | 1.1.0 |
gratis Generating Time Series with Diverse and Controllable Characteristics | 1.0.5 | 1.0.5 |
gravitas Explore Probability Distributions for Bivariate Temporal Granularities | 0.1.3 | 0.1.3 |
gravity Estimation Methods for Gravity Models | 1.1 | 1.1 |
grDevices | 4.4.1 | 4.4.1 |
greeks Sensitivities of Prices of Financial Options and Implied Volatilites | 1.3.2 | 1.3.2 |
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 | 2.0.0 | 2.0.0 |
grf Generalized Random Forests | 2.3.1 | 2.3.1 |
grid The Grid Graphics Package | 4.4.1 | 4.4.1 |
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 |
gridSVG Export 'grid' Graphics as SVG | 1.7-5 | 1.7-5 |
gridtext Improved Text Rendering Support for 'Grid' Graphics | 0.1.5 | 0.1.5 |
grImport2 Importing 'SVG' Graphics | 0.3-1 | 0.3-1 |
grnn General regression neural network | 0.1.0 | 0.1.0 |
groundhog Version-Control for CRAN, GitHub, and GitLab Packages | 3.1.2 | 3.1.2 |
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 | 0.16 | 0.16 |
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 |
grwat River Hydrograph Separation and Analysis | 0.0.4 | 0.0.4 |
GSA Gene Set Analysis | ||
gsarima Two Functions for Generalized SARIMA Time Series Simulation | 0.1-5 | 0.1-5 |
gsDesign Group Sequential Design | ||
GSE Robust Estimation in the Presence of Cellwise and Casewise Contamination and Missing Data | 4.2-1 | 4.2-1 |
GSEABase | ||
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 |
gsignal Signal Processing | 0.3-5 | 0.3-5 |
gsisdecoder High Efficient Functions to Decode NFL Player IDs | 0.0.1 | 0.0.1 |
gsl Wrapper for the Gnu Scientific Library | 2.1-8 | 2.1-8 |
gslnls GSL Nonlinear Least-Squares Fitting | 1.2.0 | 1.2.0 |
GSM Gamma Shape Mixture | 1.3.2 | 1.3.2 |
GSODR Global Surface Summary of the Day ('GSOD') Weather Data Client | 3.1.9 | 3.1.9 |
gson Base Class and Methods for 'gson' Format | 0.1.0 | 0.1.0 |
gss General Smoothing Splines | 2.2-7 | 2.2-7 |
GSSE Genotype-Specific Survival Estimation | 0.1 | 0.1 |
gstat Spatial and Spatio-Temporal Geostatistical Modelling, Prediction and Simulation | 2.1-1 | 2.1-1 |
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 | 0.10.0 | 0.10.0 |
gtable Arrange 'Grobs' in Tables | 0.3.4 | 0.3.4 |
gte Generalized Turnbull's Estimator | 1.2-3 | 1.2-3 |
gtfs2gps Converting Transport Data from GTFS Format to GPS-Like Records | 2.1-1 | 2.1-1 |
gtfsio Read and Write General Transit Feed Specification (GTFS) Files | 1.1.1 | 1.1.1 |
gtfstools General Transit Feed Specification (GTFS) Editing and Analysing Tools | 1.2.0 | 1.2.0 |
gtheory Apply Generalizability Theory with R | 0.1.2 | 0.1.2 |
gtools Various R Programming Tools | 3.9.4 | 3.9.4 |
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 | 1.7.2 | 1.7.2 |
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 | 1.8 | 1.8 |
gustave A User-Oriented Statistical Toolkit for Analytical Variance Estimation | 1.0.0 | 1.0.0 |
gvc Global Value Chains Tools | 6.4.0 | 6.4.0 |
GWI Count and Continuous Generalized Variability Indexes | 1.0.2 | 1.0.2 |
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 |
gWidgetstcltk Toolkit implementation of gWidgets for tcltk package | 0.0-55.1 | 0.0-55.1 |
GWmodel Geographically-Weighted Models | 2.3-1 | 2.3-1 |
gwrr Fits Geographically Weighted Regression Models with Diagnostic Tools | 0.2-2 | 0.2-2 |
GWSDAT GroundWater Spatiotemporal Data Analysis Tool (GWSDAT) | 3.2.0 | 3.2.0 |
h2o R Interface for the 'H2O' Scalable Machine Learning Platform | 3.36.1.2 | 3.36.1.2 |
HAC Estimation, Simulation and Visualization of Hierarchical Archimedean Copulae (HAC) | 1.1-0 | 1.1-0 |
hackeRnews Wrapper for the 'Official Hacker News' API | 0.1.0 | 0.1.0 |
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 |
haplo.stats Statistical Analysis of Haplotypes with Traits and Covariates when Linkage Phase is Ambiguous | 1.9.5 | 1.9.5 |
hardhat Construct Modeling Packages | 1.3.0 | 1.3.0 |
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 | 3.0.1 | 3.0.1 |
harmony Fast, Sensitive, and Accurate Integration of Single Cell Data | 1.1.0 | 1.1.0 |
hash Full Featured Implementation of Hash Tables/Associative Arrays/Dictionaries | 3.0.1 | 3.0.1 |
haven Import and Export 'SPSS', 'Stata' and 'SAS' Files | 2.5.4 | 2.5.4 |
hbsae Hierarchical Bayesian Small Area Estimation | 1.2 | 1.2 |
HBV.IANIGLA Modular Hydrological Model | 0.2.6 | 0.2.6 |
hda Heteroscedastic Discriminant Analysis | 0.2-14 | 0.2-14 |
hdbm High Dimensional Bayesian Mediation Analysis | 0.9.0 | 0.9.0 |
HDclassif High Dimensional Supervised Classification and Clustering | 2.2.1 | 2.2.1 |
hdf5r Interface to the 'HDF5' Binary Data Format | 1.3.9 | 1.3.9 |
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 |
HDMT A Multiple Testing Procedure for High-Dimensional Mediation Hypotheses | ||
hdnom Benchmarking and Visualization Toolkit for Penalized Cox Models | 6.0.2 | 6.0.2 |
HDO.db | 0.99.1 | 0.99.1 |
hdrcde Highest Density Regions and Conditional Density Estimation | 3.4 | 3.4 |
HDShOP High-Dimensional Shrinkage Optimal Portfolios | 0.1.3 | 0.1.3 |
HDTSA High Dimensional Time Series Analysis Tools | 1.0.2 | 1.0.2 |
HDtweedie The Lasso for Tweedie's Compound Poisson Model Using an IRLS-BMD Algorithm | 1.2 | 1.2 |
heatmaply Interactive Cluster Heat Maps Using 'plotly' and 'ggplot2' | 1.5.0 | 1.5.0 |
Heatplus | 3.10.0 | 3.10.0 |
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 | 1.6.0 | 1.6.0 |
here A Simpler Way to Find Your Files | 1.0.1 | 1.0.1 |
hermite Generalized Hermite Distribution | 1.1.2 | 1.1.2 |
hett Heteroscedastic t-Regression | 0.3-3 | 0.3-3 |
hexbin Hexagonal Binning Routines | 1.28.3 | 1.28.3 |
hexView Viewing Binary Files | 0.3-4 | 0.3-4 |
hglm.data Data for the 'hglm' Package | 1.0-1 | 1.0-1 |
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 |
hierfstat Estimation and Tests of Hierarchical F-Statistics | 0.5-11 | 0.5-11 |
highcharter A Wrapper for the 'Highcharts' Library | 0.9.4 | 0.9.4 |
highfrequency Tools for Highfrequency Data Analysis | 1.0.1 | 1.0.1 |
highlight Syntax Highlighter | 0.5.1 | 0.5.1 |
highr Syntax Highlighting for R Source Code | 0.10 | 0.10 |
highs 'HiGHS' Optimization Solver | 0.1-10 | 0.1-10 |
HIMA High-Dimensional Mediation Analysis | ||
hipread Read Hierarchical Fixed Width Files | 0.2.4 | 0.2.4 |
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 |
Hmisc Harrell Miscellaneous | 5.1-1 | 5.1-1 |
hms Pretty Time of Day | 1.1.3 | 1.1.3 |
hNMF Hierarchical Non-Negative Matrix Factorization | 1.0 | 1.0 |
hoardr Manage Cached Files | 0.5.4 | 0.5.4 |
homals Gifi Methods for Optimal Scaling | 1.0-10 | 1.0-10 |
hommel Methods for Closed Testing with Simes Inequality, in Particular Hommel's Method | 1.6 | 1.6 |
homologene Quick Access to Homologene and Gene Annotation Updates | 1.4.68.19.3.27 | 1.4.68.19.3.27 |
hoopR Access Men's Basketball Play by Play Data | 2.1.0 | 2.1.0 |
hot.deck Multiple Hot Deck Imputation | 1.2 | 1.2 |
howzatR Useful Functions for Cricket Analysis | 1.0.1 | 1.0.1 |
HPO.db A set of annotation maps describing the Human Phenotype Ontology | 0.99.2 | 0.99.2 |
hqreg Regularization Paths for Lasso or Elastic-Net Penalized Huber Loss Regression and Quantile Regression | 1.4 | 1.4 |
hrbrthemes Additional Themes, Theme Components and Utilities for 'ggplot2' | 0.8.0 | 0.8.0 |
hrqglas Group Variable Selection for Quantile and Robust Mean Regression | 1.1.0 | 1.1.0 |
HSAUR3 A Handbook of Statistical Analyses Using R (3rd Edition) | 1.0-14 | 1.0-14 |
htm2txt Convert Html into Text | 2.2.2 | 2.2.2 |
htmlTable Advanced Tables for Markdown/HTML | 2.4.2 | 2.4.2 |
htmltidy Tidy Up and Test XPath Queries on HTML and XML Content | 0.5.0 | 0.5.0 |
htmltools Tools for HTML | 0.5.7 | 0.5.7 |
HTMLUtils Facilitates Automated HTML Report Creation | 0.1.9 | 0.1.9 |
htmlwidgets HTML Widgets for R | 1.6.4 | 1.6.4 |
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 | 4.2.2 | 4.2.2 |
httpuv HTTP and WebSocket Server Library | 1.6.14 | 1.6.14 |
httr Tools for Working with URLs and HTTP | 1.4.7 | 1.4.7 |
httr2 Perform HTTP Requests and Process the Responses | 1.0.0 | 1.0.0 |
huge High-Dimensional Undirected Graph Estimation | 1.3.5 | 1.3.5 |
humanFormat Human-Friendly Formatting Functions | 1.2 | 1.2 |
humanize Create Values for Human Consumption | 0.2.0 | 0.2.0 |
humidity Calculate Water Vapor Measures from Temperature and Dew Point | 0.1.5 | 0.1.5 |
hunspell High-Performance Stemmer, Tokenizer, and Spell Checker | 3.0.3 | 3.0.3 |
hutils Miscellaneous R Functions and Aliases | 1.8.1 | 1.8.1 |
huxtable Easily Create and Style Tables for LaTeX, HTML and Other Formats | 5.5.3 | 5.5.3 |
hwriter HTML Writer - Outputs R Objects in HTML Format | 1.3.2.1 | 1.3.2.1 |
hwwntest Tests of White Noise using Wavelets | 1.3.2 | 1.3.2 |
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 | 0.5-4 | 0.5-4 |
hydroloom Utilities to Weave Hydrologic Fabrics | 1.0.2 | 1.0.2 |
HydroMe Estimating Water Retention and Infiltration Model Parameters using Experimental Data | 2.0-1 | 2.0-1 |
hydropeak Detect and Characterize Sub-Daily Flow Fluctuations | 0.1.2 | 0.1.2 |
hydroPSO Particle Swarm Optimisation, with Focus on Environmental Models | 0.5-1 | 0.5-1 |
hydroroute Trace Longitudinal Hydropeaking Waves | 0.1.2 | 0.1.2 |
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 |
hydrotoolbox Hydrological Tools for Handling Hydro-Meteorological Data Records | 1.1.2 | 1.1.2 |
hydroTSM Time Series Management, Analysis and Interpolation for Hydrological Modelling | 0.7-0 | 0.7-0 |
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 | 0.6-5 | 0.6-5 |
hypergeo The Gauss Hypergeometric Function | 1.2-13 | 1.2-13 |
HypergeoMat Hypergeometric Function of a Matrix Argument | 4.0.2 | 4.0.2 |
hypervolume High Dimensional Geometry, Set Operations, Projection, and Inference Using Kernel Density Estimation, Support Vector Machines, and Convex Hulls | 3.0.4 | 3.0.4 |
i2extras Functions to Work with 'incidence2' Objects | 0.2.1 | 0.2.1 |
iai Interface to 'Interpretable AI' Modules | 1.10.0 | 1.10.0 |
iarm Item Analysis in Rasch Models | 0.4.3 | 0.4.3 |
ibd Incomplete Block Designs | 1.5 | 1.5 |
ibdreg Regression Methods for IBD Linkage with Covariates | ||
ibelief Belief Function Implementation | 1.3.1 | 1.3.1 |
ibmdbR IBM in-Database Analytics for R | 1.51.0 | 1.51.0 |
iBreakDown Model Agnostic Instance Level Variable Attributions | 2.1.2 | 2.1.2 |
IBrokers R API to Interactive Brokers Trader Workstation | 0.10-2 | 0.10-2 |
ica Independent Component Analysis | 1.0-3 | 1.0-3 |
ICAOD Optimal Designs for Nonlinear Statistical Models by Imperialist Competitive Algorithm (ICA) | 1.0.1 | 1.0.1 |
icarus Calibrates and Reweights Units in Samples | 0.3.2 | 0.3.2 |
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 |
ICEbox Individual Conditional Expectation Plot Toolbox | 1.1.5 | 1.1.5 |
iCellR Analyzing High-Throughput Single Cell Sequencing Data | 1.6.5 | 1.6.5 |
icenReg Regression Models for Interval Censored Data | 2.0.16 | 2.0.16 |
Icens NPMLE for Censored and Truncated Data | ||
icensmis Study Design and Data Analysis in the Presence of Error-Prone Diagnostic Tests and Self-Reported Outcomes | 1.5.0 | 1.5.0 |
ICGE Estimation of Number of Clusters and Identification of Atypical Units | 0.4.2 | 0.4.2 |
ICGOR Fit Generalized Odds Rate Hazards Model with Interval Censored Data | 2.0 | 2.0 |
ichimoku Visualization and Tools for Ichimoku Kinko Hyo Strategies | 1.4.13 | 1.4.13 |
icRSF A Modified Random Survival Forest Algorithm | 1.2 | 1.2 |
ICS Tools for Exploring Multivariate Data via ICS/ICA | 1.4-1 | 1.4-1 |
ICSNP Tools for Multivariate Nonparametrics | 1.1-2 | 1.1-2 |
ICsurv Semiparametric Regression Analysis of Interval-Censored Data | 1.0.1 | 1.0.1 |
icsw Inverse Compliance Score Weighting | 1.0.0 | 1.0.0 |
ICtest Estimating and Testing the Number of Interesting Components in Linear Dimension Reduction | 0.3-5 | 0.3-5 |
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 |
idefix Efficient Designs for Discrete Choice Experiments | 1.0.3 | 1.0.3 |
idem Inference in Randomized Controlled Trials with Death and Missingness | 5.2 | 5.2 |
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 |
ie2misc Irucka Embry's Miscellaneous USGS Functions | 0.9.1 | 0.9.1 |
ifaTools Toolkit for Item Factor Analysis with 'OpenMx' | 0.23 | 0.23 |
igcop Computational Tools for the IG and IGL Copula Families | 1.0.2 | 1.0.2 |
igraph Network Analysis and Visualization | 2.0.1.1 | 2.0.1.1 |
illuminaio | ||
imbibe A Pipe-Friendly Image Calculator | 0.1.1 | 0.1.1 |
imguR An Imgur.com API Client Package | 1.0.3 | 1.0.3 |
IMIFA Infinite Mixtures of Infinite Factor Analysers and Related Models | 2.1.10 | 2.1.10 |
immer Item Response Models for Multiple Ratings | 1.4-15 | 1.4-15 |
imp4p Imputation for Proteomics | 1.2 | 1.2 |
impimp Imprecise Imputation for Statistical Matching | 0.3.1 | 0.3.1 |
implied Convert Between Bookmaker Odds and Probabilities | 0.5 | 0.5 |
implyr R Interface for Apache Impala | 0.4.0 | 0.4.0 |
import An Import Mechanism for R | 1.3.2 | 1.3.2 |
impute impute: Imputation for microarray data | ||
imputeFin Imputation of Financial Time Series with Missing Values and/or Outliers | 0.1.2 | 0.1.2 |
imputeMulti Imputation Methods for Multivariate Multinomial Data | 0.8.4 | 0.8.4 |
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 |
inca Integer Calibration | 0.0.4 | 0.0.4 |
IncDTW Incremental Calculation of Dynamic Time Warping | 1.1.4.4 | 1.1.4.4 |
incidence Compute, Handle, Plot and Model Incidence of Dated Events | 1.7.3 | 1.7.3 |
incidence2 Compute, Handle and Plot Incidence of Dated Events | 2.2.3 | 2.2.3 |
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 | 1.0.6 | 1.0.6 |
inferference Methods for Causal Inference with Interference | 1.0.2 | 1.0.2 |
inflection Finds the Inflection Point of a Curve | 1.3.6 | 1.3.6 |
influence.SEM Case Influence in Structural Equation Models | 2.3 | 2.3 |
influxdbr R Interface to InfluxDB | 0.14.2 | 0.14.2 |
InformativeCensoring Multiple Imputation for Informative Censoring | 0.3.6 | 0.3.6 |
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 | 0.5.5 | 0.5.5 |
insee Tools to Easily Download Data from INSEE BDM Database | 1.1.5 | 1.1.5 |
insight Easy Access to Model Information for Various Model Objects | 0.19.8 | 0.19.8 |
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 | 1.5-7 | 1.5-7 |
intccr Semiparametric Competing Risks Regression under Interval Censoring | 3.0.4 | 3.0.4 |
interactiveDisplayBase | 1.36.0 | 1.36.0 |
interflex Multiplicative Interaction Models Diagnostics and Visualization | 1.2.6 | 1.2.6 |
interleave Converts Tabular Data to Interleaved Vectors | 0.1.2 | 0.1.2 |
interp Interpolation Methods | 1.1-6 | 1.1-6 |
interval Weighted Logrank Tests and NPMLE for Interval Censored Data | ||
intervals Tools for Working with Points and Intervals | 0.15.4 | 0.15.4 |
IntervalSurgeon Operating on Integer-Bounded Intervals | 1.1 | 1.1 |
intsurv Integrative Survival Modeling | 0.2.2 | 0.2.2 |
inum Interval and Enum-Type Representation of Vectors | 1.0-5 | 1.0-5 |
InvariantCausalPrediction Invariant Causal Prediction | 0.8 | 0.8 |
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 |
iotools I/O Tools for Streaming | 0.3-5 | 0.3-5 |
ipaddress Data Analysis for IP Addresses and Networks | 1.0.2 | 1.0.2 |
ipcwswitch Inverse Probability of Censoring Weights to Deal with Treatment Switch in Randomized Clinical Trials | 1.0.4 | 1.0.4 |
ipdw Spatial Interpolation by Inverse Path Distance Weighting | 2.0-0 | 2.0-0 |
ipfp Fast Implementation of the Iterative Proportional Fitting Procedure in C | 1.0.2 | 1.0.2 |
ipred Improved Predictors | 0.9-14 | 0.9-14 |
iptools Manipulate, Validate and Resolve 'IP' Addresses | 0.7.2 | 0.7.2 |
ipumsr Read 'IPUMS' Extract Files | 0.7.0 | 0.7.0 |
ipw Estimate Inverse Probability Weights | 1.2.1 | 1.2.1 |
IPWboxplot Adapted Boxplot to Missing Observations | 0.1.2 | 0.1.2 |
iqLearn Interactive Q-Learning | 1.5 | 1.5 |
irace Iterated Racing for Automatic Algorithm Configuration | 3.5 | 3.5 |
IRanges | 2.36.0 | 2.36.0 |
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 |
irr Various Coefficients of Interrater Reliability and Agreement | 0.84.1 | 0.84.1 |
irrNA Coefficients of Interrater Reliability – Generalized for Randomly Incomplete Datasets | 0.2.3 | 0.2.3 |
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 |
irtplay | 1.6.5 | 1.6.5 |
irtrees Estimation of Tree-Based Item Response Models | 1.0.0 | 1.0.0 |
IRTShiny Item Response Theory via Shiny | 1.2 | 1.2 |
Iscores Proper Scoring Rules for Missing Value Imputation | 1.1.0 | 1.1.0 |
isdparser Parse 'NOAA' Integrated Surface Data Files | 0.4.0 | 0.4.0 |
IsingFit Fitting Ising Models Using the ELasso Method | 0.4 | 0.4 |
IsingSampler Sampling Methods and Distribution Functions for the Ising Model | 0.2.3 | 0.2.3 |
islasso The Induced Smoothed Lasso | 1.5.2 | 1.5.2 |
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 |
isni Index of Local Sensitivity to Nonignorability | 1.3 | 1.3 |
Iso Functions to Perform Isotonic Regression | 0.0-21 | 0.0-21 |
isoband Generate Isolines and Isobands from Regularly Spaced Elevation Grids | 0.2.6 | 0.2.6 |
ISOcodes Selected ISO Codes | 2023.12.07 | 2023.12.07 |
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 | 0.5.20 | 0.5.20 |
isoWater Discovery, Retrieval, and Analysis of Water Isotope Data | 1.1.2 | 1.1.2 |
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 |
iterators Provides Iterator Construct | 1.0.14 | 1.0.14 |
iterLap Approximate Probability Densities by Iterated Laplace Approximations | 1.1-4 | 1.1-4 |
iterpc Efficient Iterator for Permutations and Combinations | 0.4.2 | 0.4.2 |
itertools Iterator Tools | 0.1-3 | 0.1-3 |
ITRLearn Statistical Learning for Individualized Treatment Regime | 1.0-1 | 1.0-1 |
ITRSelect Variable Selection for Optimal Individualized Dynamic Treatment Regime | 1.0-1 | 1.0-1 |
itscalledsoccer American Soccer Analysis API Client | 0.2.4 | 0.2.4 |
ivfixed Instrumental fixed effect panel data model | 1.0 | 1.0 |
ivmodel Statistical Inference and Sensitivity Analysis for Instrumental Variables Model | 1.9.1 | 1.9.1 |
ivmte Instrumental Variables: Extrapolation by Marginal Treatment Effects | 1.4.0 | 1.4.0 |
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 |
ivreg Instrumental-Variables Regression by '2SLS', '2SM', or '2SMM', with Diagnostics | 0.6-2 | 0.6-2 |
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 | 2.0-4 | 2.0-4 |
jagsUI A Wrapper Around 'rjags' to Streamline 'JAGS' Analyses | 1.6.2 | 1.6.2 |
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 |
jjb Balamuta Miscellaneous | 0.1.1 | 0.1.1 |
JM Joint Modeling of Longitudinal and Survival Data | 1.5-2 | 1.5-2 |
JMbayes Joint Modeling of Longitudinal and Time-to-Event Data under a Bayesian Approach | 0.8-85 | 0.8-85 |
JMdesign Joint Modeling of Longitudinal and Survival Data - Power Calculation | 1.5 | 1.5 |
jmvcore Dependencies for the 'jamovi' Framework | 2.4.7 | 2.4.7 |
joineR Joint Modelling of Repeated Measurements and Time-to-Event Data | 1.2.8 | 1.2.8 |
joineRML Joint Modelling of Multivariate Longitudinal Data and Time-to-Event Outcomes | 0.4.6 | 0.4.6 |
joinet Multivariate Elastic Net Regression | 0.0.10 | 0.0.10 |
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 | 1.0.5 | 1.0.5 |
JointModel Semiparametric Joint Models for Longitudinal and Counting Processes | 1.0 | 1.0 |
jomo Multilevel Joint Modelling Multiple Imputation | 2.7-6 | 2.7-6 |
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 | 0.1-10 | 0.1-10 |
jqr Client for 'jq', a 'JSON' Processor | 1.3.3 | 1.3.3 |
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 | 1.1.2 | 1.1.2 |
js Tools for Working with JavaScript in R | 1.2 | 1.2 |
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 | 1.8.8 | 1.8.8 |
jsonvalidate Validate 'JSON' Schema | 1.3.2 | 1.3.2 |
jstor Read Data from JSTOR/DfR | 0.3.11 | 0.3.11 |
jtools Analysis and Presentation of Social Scientific Data | 2.2.0 | 2.2.0 |
juicr Automated and Manual Extraction of Numerical Data from Scientific Images | 0.1 | 0.1 |
juicyjuice Inline CSS Properties into HTML Tags Using 'juice' | 0.1.0 | 0.1.0 |
JuliaCall Seamless Integration Between R and 'Julia' | 0.17.5 | 0.17.5 |
JuliaConnectoR A Functionally Oriented Interface for Integrating 'Julia' with R | 1.1.3 | 1.1.3 |
JumpeR Importing and Working with Track and Field Data | 0.3.0 | 0.3.0 |
JWileymisc Miscellaneous Utilities and Functions | 1.3.0 | 1.3.0 |
kableExtra Construct Complex Table with 'kable' and Pipe Syntax | 1.4.0 | 1.4.0 |
kalmanfilter Kalman Filter | 2.0.2 | 2.0.2 |
kaos Encoding of Sequences Based on Frequency Matrix Chaos Game Representation | 0.1.2 | 0.1.2 |
kappaSize Sample Size Estimation Functions for Studies of Interobserver Agreement | 1.2 | 1.2 |
kaps K-Adaptive Partitioning for Survival data | 1.0.2 | 1.0.2 |
kcirt k-Cube Thurstonian IRT Models | 0.6.0 | 0.6.0 |
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 | 1.42.0 | 1.42.0 |
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' | 2.13.0 | 2.13.0 |
kernelboot Smoothed Bootstrap and Random Generation from Kernel Densities | 0.1.10 | 0.1.10 |
Kernelheaping Kernel Density Estimation for Heaped and Rounded Data | 2.3.0 | 2.3.0 |
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 |
Keyboard Bayesian Designs for Early Phase Clinical Trials | 0.1.3 | 0.1.3 |
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 | 1.5.1 | 1.5.1 |
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 |
kinship2 Pedigree Functions | 1.9.6 | 1.9.6 |
kitagawa Spectral Response of Water Wells to Harmonic Strain and Pressure Signals | 3.1.2 | 3.1.2 |
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 | 1.7-1 | 1.7-1 |
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 | 0.4-2 | 0.4-2 |
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 | 2.4.6.1 | 2.4.6.1 |
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 | 1.45 | 1.45 |
knn.covertree An Accurate kNN Implementation with Multiple Distance Measures | 1.0 | 1.0 |
kofnGA A Genetic Algorithm for Fixed-Size Subset Selection | 1.3 | 1.3 |
kohonen Supervised and Unsupervised Self-Organising Maps | 3.0.12 | 3.0.12 |
KONPsurv KONP Tests: Powerful K-Sample Tests for Right-Censored Data | 1.0.4 | 1.0.4 |
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 |
KRIS Keen and Reliable Interface Subroutines for Bioinformatic Analysis | 1.1.6 | 1.1.6 |
ks Kernel Smoothing | 1.14.2 | 1.14.2 |
kSamples K-Sample Rank Tests and their Combinations | 1.2-10 | 1.2-10 |
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 | 1.3.1 |
kutils Project Management Tools | 1.73 | 1.73 |
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 | 2024.1-30 | 2024.1-30 |
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 | 2.1-0 | 2.1-0 |
label.switching Relabelling MCMC Outputs of Mixture Models | 1.8 | 1.8 |
labeling Axis Labeling | 0.4.3 | 0.4.3 |
labelled Manipulating Labelled Data | 2.12.0 | 2.12.0 |
labelVector Label Attributes for Atomic Vectors | 0.1.2 | 0.1.2 |
laeken Estimation of Indicators on Social Exclusion and Poverty | 0.5.3 | 0.5.3 |
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 |
laGP Local Approximate Gaussian Process Regression | 1.5-9 | 1.5-9 |
Lahman Sean 'Lahman' Baseball Database | 11.0-0 | 11.0-0 |
lakemorpho Lake Morphometry Metrics | 1.3.2 | 1.3.2 |
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 | 0.6.9-1 | 0.6.9-1 |
lamW Lambert-W Function | 2.2.2 | 2.2.2 |
landest Landmark Estimation of Survival and Treatment Effect | 1.2 | 1.2 |
landsat Radiometric and Topographic Correction of Satellite Imagery | 1.1.0 | 1.1.0 |
landscapemetrics Landscape Metrics for Categorical Map Patterns | 2.1.1 | 2.1.1 |
languagelayeR Access the 'languagelayer' API | 1.2.4 | 1.2.4 |
languageserver Language Server Protocol | 0.3.13 | 0.3.13 |
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 | 1.3.2 | 1.3.2 |
latex2exp Use LaTeX Expressions in Plots | 0.9.6 | 0.9.6 |
lattice Trellis Graphics for R | 0.22-5 | 0.22-5 |
latticeExtra Extra Graphical Utilities Based on Lattice | 0.6-30 | 0.6-30 |
LatticeKrig Multi-Resolution Kriging Based on Markov Random Fields | 8.4 | 8.4 |
lava Latent Variable Models | 1.7.3 | 1.7.3 |
lavaan Latent Variable Analysis | 0.6-15 | 0.6-15 |
lavaan.survey Complex Survey Structural Equation Modeling (SEM) | ||
lavaSearch2 Tools for Model Specification in the Latent Variable Framework | 1.5.6 | 1.5.6 |
LAWBL Latent (Variable) Analysis with Bayesian Learning | 1.5.0 | 1.5.0 |
lawstat Tools for Biostatistics, Public Policy, and Law | 3.6 | 3.6 |
lazyeval Lazy (Non-Standard) Evaluation | 0.2.2 | 0.2.2 |
lazyWeave LaTeX Wrappers for R Users | 3.0.2 | 3.0.2 |
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 | 2020-3.3 | 2020-3.3 |
lbiassurv Length-biased correction to survival curve estimation. | 1.1 | 1.1 |
LCAvarsel Variable Selection for Latent Class Analysis | 1.1 | 1.1 |
lcmm Extended Mixed Models Using Latent Classes and Latent Processes | 2.1.0 | 2.1.0 |
lcopula Liouville Copulas | 1.0.7 | 1.0.7 |
lctools Local Correlation, Spatial Inequalities, Geographically Weighted Regression and Other Tools | 0.2-8 | 0.2-8 |
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 | 2.0.2 | 2.0.2 |
leafem 'leaflet' Extensions for 'mapview' | 0.2.3 | 0.2.3 |
leafgl High-Performance 'WebGl' Rendering for Package 'leaflet' | 0.1.1 | 0.1.1 |
leaflet Create Interactive Web Maps with the JavaScript 'Leaflet' Library | 2.2.1 | 2.2.1 |
leaflet.extras Extra Functionality for 'leaflet' Package | 1.0.0 | 1.0.0 |
leaflet.extras2 Extra Functionality for 'leaflet' Package | 1.2.0 | 1.2.0 |
leaflet.providers Leaflet Providers | 2.0.0 | 2.0.0 |
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 |
legion Forecasting Using Multivariate Models | 0.1.2 | 0.1.2 |
leiden R Implementation of Leiden Clustering Algorithm | 0.4.3.1 | 0.4.3.1 |
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 |
lgarch Simulation and Estimation of Log-GARCH Models | 0.6-2 | 0.6-2 |
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 | 1.0-10 | 1.0-10 |
libgeos Open Source Geometry Engine ('GEOS') C API | 3.11.1-2 | 3.11.1-2 |
LiblineaR Linear Predictive Models Based on the LIBLINEAR C/C++ Library | 2.10-23 | 2.10-23 |
librarian Install, Update, Load Packages from CRAN, 'GitHub', and 'Bioconductor' in One Step | 1.8.1 | 1.8.1 |