Awesome R

Microsoft's free & open-source editor, TypeScript friendly, VSCode Plugins. ![Open-Source Software][OSS Icon] ![Freeware][Freeware Icon] ![Awesome List][awesome-list Icon]

Microsoft's free & open-source editor, TypeScript friendly, VSCode Plugins. ![Open-Source Software][OSS Icon] ![Freeware][Freeware Icon] ![Awesome List][awesome-list Icon]

A powerful and productive user interface for R. Works great on Windows, Mac, and Linux.

Emacs Speaks Statistics is an add-on package for emacs text editors.

An Eclipse based IDE for R.

Revolution R would be offered free to academic users and commercial software would focus on big data, large scale multiprocessor functionality.

A package that provides a basic graphical user interface.

A Menu driven data analysis GUI with a spreadsheet like data editor.

A platform-independent browser-based interface for business analytics in R, based on the Shiny.

and JASP - Desktop software for both Bayesian and Frequentist methods, using a UI familiar to SPSS users.

An IDE contains tools for model creation, scientific image analysis and statistical analysis for ecological modelling.

R Tools for Visual Studio.

An extensible IDE/GUI for R.

Data structures designed to store large datasets.

Showcases of ggplot2 extensions.

3D visualization device system for R.

R graphics device using cairo graphics library for creating high-quality display output.

Powerful functions to deal with 3d plots, isosurfaces, etc.

Use xkcd style in graphs.

An image processing package based on CImg library to work with images and display them.

R Interface to D3 Visualizations

Plotting Multi-Dimensional Data

Plotting Multi-Dimensional Data - Using 'rgl'

Displays R matrices or data frames as interactive HTML tables.

One of the most popular JavaScript libraries interactive maps.

Enables easy creation of D3 scatterplots, line charts, and histograms.

D3 JavaScript Network Graphs from R.

R Interface to Bokeh.

Export tables to LaTeX or HTML.

An R templating system.

Dynamic documents for R.

A package designed to write LaTeX reports using R.

Pre-compute data to enhance your report templates. Can be combined with knitr.

An R package to generate Microsoft Word, Microsoft PowerPoint and HTML reports.

An R package to embed complex tables (merged cells, multi-level headers and footers, conditional formatting) in Microsoft Word, Microsoft PowerPoint and HTML reports. It cooperates with the [officer] package and integrates with [rmarkdown] reports.

Authoring Books with R Markdown.

A package to design flexible and reproducible deployment workflows for R.

Build fancy HTML or 'LaTeX' tables using 'kable()' from 'knitr'.

General network (HTTP/FTP/...) client interface for R.

Tools for parsing and generating XML within R.

Optimized tools for parsing and generating XML within R.

HTTP API for R handling concurrent calls, based on the Apache2 web server, to expose R code as REST web services and create full-sized, multi-page web applications.

R started with release 2.14.0 which includes a new package parallel incorporating (slightly revised) copies of packages multicore and snow.

Rmpi provides an interface (wrapper) to MPI APIs. It also provides interactive R slave environment.

Executing the loop in parallel.

A minimal, efficient, cross-platform unified Future API for parallel and distributed processing in R; designed for beginners as well as advanced developers.

R interface for Apache Spark from RStudio.

High performance computing with LSF, TORQUE, Slurm, OpenLava, SGE and Docker Swarm.

Rcpp provides a powerful API on top of R, make function in R extremely faster.

speeding up your R code using the JIT

Low-level R to Java interface.

R interface to Python via Jython.

Package allowing R to call Python.

a Ruby library that integrates the R interpreter in Ruby.

Read and write of MAT files together with R-to-MATLAB connectivity.

A bidirectional interface for calling R from Perl and Perl from R.

Bring the best of JavaScript data visualization to R.

Python interface for R.

ODBC database access for R.

R interface to the MySQL database.

OCI based Oracle database interface for R.

R interface to the PostgreSQL database system.

SQLite interface for R

Provides access to databases through the JDBC interface.

Direct interface (not Java) to the most basic functionality of Apache Cassandra.

Regularization for semiparametric additive hazards regression.

Mining Association Rules and Frequent Itemsets

Big Random Forests: Classification and Regression Forests for

Generalized Ridge Regression (with special advantage for p >> n

Bundle Methods for Regularized Risk Minimization Package

A wrapper algorithm for all-relevant feature selection

Gradient Boosting

C5.0 Decision Trees and Rule-Based Models

Classification and Regression Training

Classification, regression, feature evaluation and ordinal

Cox models by likelihood based boosting for a single survival

Rule- and Instance-Based Regression Modeling

Misc Functions of the Department of Statistics (e1071), TU Wien

Multivariate Adaptive Regression Spline Models

Elastic-Net for Sparse Estimation and Sparse PCA

Data sets, functions and examples from the book: "The Elements

Evolutionary Learning of Globally Optimal Trees

A feature selection framework, based on subset-search or feature ranking approches.

Fuzzy Rule-based Systems for Classification and Regression Tasks

Generalized linear and additive models by likelihood based

Boosting Methods for GAMLSS

Generalized Boosted Regression Models

Lasso and elastic-net regularized generalized linear models

L1 Regularization Path for Generalized Linear Models and Cox

Likelihood-based Boosting for Generalized mixed models

Fitting user specified models with Group Lasso penalty

Regularization paths for regression models with grouped

Deeplearning, Random forests, GBM, KMeans, PCA, GLM

Heteroscedastic Discriminant Analysis

Improved Predictors

kernlab: Kernel-based Machine Learning Lab

Classification and visualization

Supervised and Unsupervised Self-Organising Maps.

Fast algorithms for best subset selection

Least Angle Regression, Lasso and Forward Stagewise

L1 constrained estimation aka ‘lasso’

Linear Predictive Models Based On The Liblinear C/C++ Library

Mixed-effects models, handling user-specified matrix of residual covariance, relevant for the anaysis of repeated observations in longitudinal trials

Generalized mixed-effects models, handling user-specified matrix of residual covariance, relevant for the anaysis of repeated observations in longitudinal trials

Logic Regression

Mapping, pruning, and graphing tree models

Model-Based Boosting

Multivariate partitioning

Regularization paths for SCAD- and MCP-penalized regression

eed-forward Neural Networks and Multinomial Log-Linear Models

Oblique Trees for Classification Data

Pam: prediction analysis for microarrays

A Laboratory for Recursive Partytioning

A Toolkit for Recursive Partytioning

L1 (lasso and fused lasso) and L2 (ridge) penalized estimation

Penalized classification using Fisher's linear discriminant

Feature Selection SVM using penalty functions

quantregForest: Quantile Regression Forests

randomForest: Breiman and Cutler's random forests for classification and regression.

randomForestSRC: Random Forests for Survival, Regression and Classification (RF-SRC).

Graphical user interface for data mining in R.

Shrunken Centroids Regularized Discriminant Analysis

Relevant Dimension Estimation (RDE) in Feature Spaces

Regression Trees with Random Effects for Longitudinal (Panel)

Relaxed Lasso

R version of GENetic Optimization Using Derivatives

R genetic programming framework

Continuous Optimization using Memetic Algorithms with Local

Simpler use of data mining methods (e.g. NN and SVM) in

Visualizing the performance of scoring classifiers

Data Analysis Using Rough Set and Fuzzy Rough Set Theories

Recursive Partitioning and Regression Trees

Recursively Partitioned Mixture Model

Neural Networks in R using the Stuttgart Neural Network

Parallel implementation of self-organizing maps.

R/Weka interface

RXshrink: Maximum Likelihood Shrinkage via Generalized Ridge or Least

Shrinkage Discriminant Analysis and CAT Score Variable Selection

Stepwise Diagonal Discriminant Analysis

Survival Analysis

svmpath: the SVM Path algorithm

Bayesian treed Gaussian process models

Classification and regression trees

Variable selection using random forests

A comprehensive text mining framework for R.

Apache OpenNLP Tools Interface.

An R Package for Text Analysis.

Statistical models for word frequency distributions.

Basic functions for Natural Language Processing.

Topic modeling interface to the C code developed by by David M. Blei for Topic Modeling (Latent Dirichlet Allocation (LDA), and Correlated Topics Models (CTM)).

Extracts sentiment from text using three different sentiment dictionaries.

Snowball stemmers based on the C libstemmer UTF-8 library.

Implementing tidy principles of Hadley Wickham to text mining.

Output analysis and diagnostics for MCMC.

Markov Chain Monte Carlo.

Markov chain Monte Carlo (MCMC) Package.

Running WinBUGS and OpenBUGS from R / S-PLUS.

R interface to the OpenBUGS MCMC software.

R interface to the JAGS MCMC library.

R interface to the Stan MCMC software.

Interface to Lp_solve to Solve Linear/Integer Programs.

Derivative-free optimization algorithms by quadratic approximation.

NLopt is a free/open-source library for nonlinear optimization.

Model mixed integer linear programs in an algebraic way directly in R.

R/GNU Linear Programming Kit Interface

The R Optimization Infrastructure ('ROI') is a sophisticated framework for handling optimization problems in R.

Quantitative Financial Modelling & Trading Framework for R.

Public Economic Data and Quantitative Analysis

Functions and data to construct technical trading rules with R.

Econometric tools for performance and risk analysis.

S3 Infrastructure for Regular and Irregular Time Series.

eXtensible Time Series.

Time series analysis and computational finance.

Analysing and Modelling Financial Assets.

Tools for the analysis and comprehension of high-throughput genomic data.

Classes and methods for handling genetic data.

An integrated package for genetic data analysis of both population and family data.

Analyses of Phylogenetics and Evolution.

Pretty heatmaps made easy.

Mixed-effects models, handling user-specified matrix of residual covariance, relevant for the anaysis of repeated observations in longitudinal trials

Generalized mixed-effects models, handling user-specified matrix of residual covariance, relevant for the anaysis of repeated observations in longitudinal trials

A collection of network analysis tools.

Basic tools to manipulate relational data in R.

Basic network measures and visualization tools.

Support for dynamic, (inter)temporal networks.

Tools to construct animated visualizations of dynamic network data in various formats.

The project behind many R network analysis packages.

Exponential random graph models in R.

Latent position and cluster models for network objects.

Network measures for weighted, two-mode and longitudinal networks.

Export network objects from R to GEXF, for manipulation with network software like Gephi or Sigma.

Spatial Analysis related resources.

One of the most popular JavaScript libraries interactive maps.

Improved Classes and Methods for Spatial Data.

Classes and Methods for Spatial Data.

Interface to Geometry Engine - Open Source

Bindings for the Geospatial Data Abstraction Library

Tools for Reading and Handling Spatial Objects

Provides color schemes for maps

Spatial Dependence: Weighting Schemes, Statistics and Models

Geographically-Weighted Models

Abstractions for Promise-Based Asynchronous Programming

A logging package emulating the python logging package.

Tools for searching and downloading data and statistics from the World Bank Data API and the World Bank Data Catalog API.

Most R packages are available through the Conda polyglot cross-platform dependency manager.

Refactorising R into C++.

FastR is an implementation of the R Language in Java atop Truffle and Graal.

a "pretty quick" implementation of R

JVM-based interpreter for the R language for the statistical analysis

TIBCO Enterprise Runtime for R.

An interactive R tutorial directly in your R console.

The R Project for Statistical Computing.

A very good introductory text on R, also covers some advanced topic. See also the Manuals section on CRAN

CRAN Contributed Documentation in many languages.

An excellent quick reference

A quick course for getting started with R.

Search through all CRAN, Bioconductor, Github packages and their archives with RDocumentation.

Find R package documentation. Try R packages in your browser.

Task Views for CRAN packages.

Create online R Jupyter Notebooks for free.

Weekly updates about R and Data Science. R Weekly is openly developed on GitHub.

There are people scattered across the Web who blog about R. This is simply an aggregator of many of those feeds.

A job board for R users (and the people who are looking to hire them)

Free book from RStudio developers with emphasis on data science workflow.

A problem-oriented online book that supports his R Graphics Cookbook, 2nd ed. (2018).

An online version of the Advanced R book.

A book (in paper and website formats) on writing R packages.

Basic analytical skills for all sorts of data in R.

More advanced data analysis that relies on R programming.

R-based methods for reproducible research and report generation.

An excellent resource for users already familiar with SAS or SPSS.

A simplified and "operational" version of The Elements of Statistical Learning. Free softcopy provided by its authors.

Patrick Burns gives insight into R's ins and outs along with its quirks!

An online version of the O’Reilly book: Efficient R Programming.

A collaborative handbook for R.

It's a good resource for systematically learning fundamentals such as types of objects, control statements, variable scope, classes and debugging in R.

A quick and simple introduction to conducting many common statistical tasks with R.

This book aims at all levels of users, with sections for beginning, intermediate and advanced R ranging from "Exploring R data structures" to running regressions and conducting factor analyses.

This series of inexpensive and focused books from Springer publish shorter books aimed at practitioners. Books can discuss the use of R in a particular subject area, such as Bayesian networks, ggplot2 and Rcpp.

Learning R as a programming language from basics to advanced topics.

The Data Science Podcast.

and @Hilary Parker.

R World News helps you keep up with happenings within the R community.

and @Jay Jacobs.

Giving practical advice on how to use R.

News and discussions of statistical software and language R.

Jasmine Dumas](https://twitter.com/jasdumas), @Ted Hart and @Mikhail Popov.

Weekly updates about R and Data Science. R Weekly is openly developed on GitHub.

Material from R for Beginners by permission of Emmanuel Paradis (Version 2 by Matt Baggott).

R Reference Card for Regression Analysis.

Reference Card for ESS.

9 courses including: Introduction to R, literate analysis tools, Shiny and some more.

Introduction to R for the Life Sciences.

Covers introduction, data handling and statistical analysis in R.