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 (1) an effective data handling and storage facility; (2) a suite of operators for calculations on arrays, in particular matrices; (3) a large, coherent, integrated collection of intermediate tools for data analysis; (4) graphical facilities for data analysis and display either on-screen or on hardcopy; and (5) 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/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 thousands more packages 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, and is now fully integrated with markdown, 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 2016 Projects

  • xingguo
    A generic computational framework for biconvex minimization toolbox in R
    Estimations of a large family of statistical models can be casted as optimizing biconvex functions over given (bi)convex sets. Our goal in this...
  • Faizan Khan
    Animint package in R allows animated data visualization using ggplot syntax. It is a useful tool for obtaining an intuitive understanding of patterns...
  • RobinKo
    Discovr: Streamlining statistical data analysis
    The discovr package will enable a fast and efficient way to test the most common statistical analysis methods. It will therefore allow users to...
  • Leopoldo Catania
    GAS package
    The GAS package for R aims to create an integrated computational environment to deal with Generalised Autoregressive Score (GAS) models. GAS models...
  • schloerke
    ggduo: pairs plots for multiple regression, cca, time series
    The function ggpairs and ggscatmat in GGally provide generalized pairs plots for a data frame in R. All pairs of variables are displayed, with plot...
  • ABelov
    Implementation of hyperspectral unmixing algorithms for unimixR package
    Hyperspectral data is often used to determine what materials are present in a scene. Materials of interest could include roadways, vegetation, and...
  • Yuqi Li
    Implementation of Recurrent Models and Examples in R for MXNet
    I aim to implement some important deep learning models in R for the MXNet package. The main component of the proposed work is the implementation of...
  • cryptomanic
    Improving markovchain R package
    This project aims to extend markovchain R package functions and capabilities in order to provide statisticians a wider range of tools to perform...
  • JanIdziak
    Integration of Text Mining and Topic Modeling Tools
    The goal of this project is to create a user friendly API for an integrated workflow to perform typical text mining, natural language processing, and...
  • Acharya
    Major Improvements to the factorAnalytics package
    This is a proposal to add and improve the functionality, usability, and graphics to each of the three main factor model types (fundamental, time...
  • Balázs Dukai
    Managing and visualizing movement data with PostGIS and R
    The project develops the integration of R and PostGIS for managing movement trajectories. The focus is on streamlining the workflow for biologists to...
  • Kbluteau
    Markov Switching GARCH models (MSGARCH)
    The goal of this project is to implement a package that will give the fi nancial community tools to estimate, simulate, and test several MSGARCH...
  • haleyj
    Mosaicplots in the ggplot2 framework: ggmosaic
    The package productplots already provides a fully functional base for creating mosaic plots based on the ggplot2 framework. I will make use of this...
  • luismurao
    NicheToolbox: from getting biodiversity data to evaluating species distribution models in a friendly GUI environment.
    NicheToolBox project will be an R package with a friendly Graphical User Interface (GUI) developed using shiny framework that aims to facilitate the...
  • Eric Hung
    plot.xts for Performance and Risk
    xts::plot.xts is a strong engine for statistical and financial charting. But quantmod, PerformanceAnalytics, PortfolioAnalytics, quantstrat and...
  • Malith Jayaweera
    postCP Package Improvement
    Improving the postCP package, writing vignettes and tests, building a user friendly interface and ensuring that postCP passes the checks so that...
  • Qin Wenfeng
    RE2 regular expressions in R
    R provides two types of regular expressions in base package, extended regular expressions (the default) with TRE and Perl-like regular expressions...
  • kcm
    Regularized interval regression
    R package for regression with general interval censored output data. This will be the first R package with support for (1) four types of censoring,...
  • akashtndn
    Rperform: performance analysis for R package code
    Rperform is a tool to help package developers analyze the performance of their R package code. It returns quantitative metrics, relating to memory...
  • Xin Chen
    Standard Error of Risk and Performance Measures for Non-Normal and Serially Correlated Asset Returns
    This project is focused on implementing methods to accurately compute the accurate standard errors of risk and performance measures in...
  • MasonGallo
    Visualization of model hyperparameter optimization curves
    The goal of this project is to provide users of the mlr package with a way to visualize what happens during the tuning process that identifies the...
  • nasyrin
    Visualization of powerful boundary detection tools
    This project will add significant functionality to the BayesBD package and increase its efficiency by optimizing code in C++.