This is a list of software and programming tools for the R programming language, including IDEs, package managers, libraries, debugging tools, numerical and scientific computing tools, and related projects.
Integrated development environments (IDEs) and editors
Graphical user interfaces
- Deducer â GUI front-end and data analysis package
- jamovi â GUI statistical environment built on R for data analysis and performing statistical tests
- Java GUI for R â cross-platform R console, script editor, and spreadsheet/data view.
- Rattle GUI â data mining GUI for R
- R Commander (Rcmdr) â basic GUI for statistics in R, often used for teaching and introductory work.
Implementations of R
- CXXR â experimental R engine with modernized C++ codebase
- FastR â R language implementation on the GraalVM
- GNU R â main implementation of R, maintained by the R Core Team, and distributed as part of the GNU Project.
- pqR â âÂÂpretty quick RâÂÂ
- Renjin â JVM-based interpreter for R
R packages
Mathematical and numerical libraries
- lme4 â linear mixed-effects models
- Matrix â sparse and dense matrix computations
- mgcv â generalized additive models
- nlme â nonlinear mixed-effects models
- numDeriv â numerical derivatives
- optim â built-in optimization functions
- optimx â provides a replacement and extension of the optim
- Rmpfr â multiple-precision floating-point arithmetic
Scientific and statistical libraries
- dplyr â data manipulation toolkit
- edgeR â differential expression analysis of RNA-seq data
- forecast â time series forecasting
- ggplot2 â data visualization based on the grammar of graphics
- phyloseq â analysis of microbiome census data
- shiny â interactive web applications
- survival â survival analysis
- tidyr â tidy data reshaping
Debugging and performance tools
- bench â accurately benchmark and analyze execution times
- lineprof â line-by-line profiling tool
- microbenchmark â benchmarking
- profvis â interactive R profiler
- Rcpp â integration of R and C++ for performance
- Rprof â built-in R profiler
Parallel and high-performance computing
- BiocParallel â parallel evaluation framework for R, used across Bioconductor packages.
- doParallel â provides a parallel backend for the foreach package, enabling easy parallel execution of R code.
- foreach â looping construct for parallel execution
- future â unified parallel and distributed computing
- parallel â built-in R package for parallel processing
- Rmpi â R interface to the Message Passing Interface
- snow â simple network of workstations
Machine learning and AI libraries
- caret â training and tuning for machine learning models
- keras â R interface to Keras deep learning
- mlbench â collection of artificial and real-world benchmark datasets for evaluating machine learning algorithms
- mlr â machine learning
- mlr3 â modern successor to mlr
- randomForest â ensemble learning using random forests
- tidymodels â collection of R packages for machine learning and modeling, designed with tidyverse principles.
- torch â R interface to PyTorch
- xgboost â gradient boosting framework with R bindings
Documentation and code analysis tools
- covr â test coverage
- lintr â static code analysis
- roxygen2 â documentation generation for R packages
- styler â code formatter for R scripts and packages
Testing frameworks
- checkmate â fast argument checks and assertions for R functions
- RUnit â implementing a standard Unit Testing framework
- testthat â unit testing framework
- tinytest â lightweight unit testing framework
See also
External links
References