R is a free software environment for statistical computing and graphics

R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes

  • an effective data handling and storage facility,
  • a suite of operators for calculations on arrays, in particular matrices,
  • a large, coherent, integrated collection of intermediate tools for data analysis,
  • graphical facilities for data analysis and display either on-screen or on hardcopy, and
  • a well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.

The term “environment” is intended to characterize it as a fully planned and coherent system, rather than an incremental accretion of very specific and inflexible tools, as is frequently the case with other data analysis software.

R, like S, is designed around a true computer language, and it allows users to add additional functionality by defining new functions. Much of the system is itself written in the R dialect of S, which makes it easy for users to follow the algorithmic choices made. For computationally-intensive tasks, C, C++ and Fortran code can be linked and called at run time. Advanced users can write C code to manipulate R objects directly.

Many users think of R as a statistics system. We prefer to think of it of an environment within which statistical techniques are implemented. R can be extended (easily) via packages. There are about eight packages supplied with the R distribution and many more are available through the CRAN family of Internet sites covering a very wide range of modern statistics.

R has its own LaTeX-like documentation format, which is used to supply comprehensive documentation, both on-line in a number of formats and in hardcopy.

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R Project for Statistical Computing 2020 Projects

  • Echo Liu
    A package for robust-GARCH model
    In the R-language, many packages exist for the estimation and forecasting of GARCH processes, including fGarch and rugarch. However, none, to our...
  • lazycipher
    Animated interactive ggplots
    The goal of this GSOC project is to implement new features for animint2 in order to make it possible to do more kinds of interactive data...
  • Anirban Chetia
    Asymptotic complexity testing framework/package
    R package developers currently use ad-hoc tests of asymptotic computational complexity via empirical timings of functions and visual diagnostic...
  • Rahul Chauhan
    bddashboard: Interactive Biodiversity Data Dashboard
    The bdverse is a family of R packages that allow users to conveniently employ R, for biodiversity data exploration, quality assessment (QA), data...
  • Akarsh Goyal
    Better solvers for SLOPE package
    SLOPE package offers implementations that solve the Sorted L-One Penalized Estimation (SLOPE) model for various objective functions. However when...
  • Claudia Nuñez Penichet
    Biological Survey Planning Considering Hutchinson’s Duality
    One of the challenges in biodiversity conservation is to complete an inventory of existing species in the world. Although various developed countries...
  • Julian Stanley
    Constrained changepoint GUI
    A Shiny web application for the gfpop R package. [...] Detecting sudden changes in data is important to a variety of fields. For example,...
  • Martynas Jočys
    Enhancing bdchecks: a biodiversity data quality checks system in R
    bdchecks has the potential to centralize the effort to develop a sustainable infrastructure for biodiversity data quality checks in R. This will...
  • Emil Sjørup
    Expanding the highfrequency package
    The highfrequency package is the go-to package for the analysis of intraday price data. The package was created as a merger of the packages RTAQ and...
  • Erick Oduniyi
    Fortification of the hyperSpec R Package
    The hyperSpec (http://hyperspec.r-forge.r-project.org/) package allows R users a suite of utilities for manipulating spectroscopic data. These...
  • Implement Authentication, Security and Streaming in gRPC for R Package
  • Chen Liang
    mAED: Multi-Stage Adaptive Enrichment Design in R
    The average cost of trials in the United States is up to $19.6 million for a Phase 2 trial and $52.9 million for a Phase 3 trial. Optimizing the...
  • Akshit Achara
    MiniZinc Interface for R
    MiniZinc is a free and open-source constraint modeling language. Constraint satisfaction and discrete optimization problems can be formulated in a...
  • Vito Lestingi
    Modeling Expected Returns with R
    The main goal of the project is to reproduce selected key findings from the empirical asset pricing literature and related investment practices....
  • Ayush
    QBLD - Quantile Regression for Binary Longitudinal Data
    This project follows Rahman and Vossmeyer (2019) as its motivating literature, and contributes to the three literatures by extending the various...
  • Rahul Saxena
    rco: The R Code Optimizer R Project for Statistical Computing-GSoC 2020
    This project aims to further bolster the rco (The R Code Optimizer) package and make it a one stop solution for rendering efficient R code. By...
  • Divyansh Chawla
    rsqliteadmin : sqlite admin tool in R shiny
    R currently supports working on SQLite databases through the RSQLite package. SQLite is a RDBMS which is light and highly efficient for small scale...
  • Sanchit Saini
    rtracklayer improvements
    rtracklayer is an Extensible framework for interacting with multiple genome browsers. The project adds the following new features for rtracklayer. ...
  • Sunny Dhoke
    The bdverse's development and QA frameworks
    The project idea is to develop a robust QA framework for bdverse. This shall consists of developing git strategies, developing bdtests...
  • Salsabila Mahdi
    Validation of Neural Network Packages
    The purpose of this GSoC project is to validate neural network packages that perform regression. It is a follow-up of a GSoC 2019 project in which we...