2024年2月29日 · R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. To download R , please choose your preferred CRAN mirror .

R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible.

R is an integrated suite of software facilities for data manipulation, calculation and graphical display. Among other things it has 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,

four manuals (R Development Core Team, 2005a,b,c,d) are mandatory: AnIntroductiontoR: A more formal introduction to data analysis with R than this chapter. RDataImport/Export: A very useful description of how to read and write various external data formats.

Download R-4.4.2 for Windows (83 megabytes, 64 bit) README on the Windows binary distribution; New features in this version

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R is very much a vehicle for newly developing methods of interactive data analysis. It has developed rapidly, and has been extended by a large collection of packages. However, most programs written in R are essentially ephemeral, written for a single piece of data analysis.

Suitable for a compact course or self-study, Computational Statistics: An Introduction to R illustrates how to use the freely available R software package for data analysis, statistical programming, and graphics.

RDQA is a R package for Qualitative Data Analysis, a free (free as freedom) qualitative analysis software application (BSD license). It works on Windows, Linux/ FreeBSD and Mac OSX platforms. RQDA is an easy to use tool to assist in the analysis of textual data.

2024年6月17日 · fda.usc provides routines for exploratory and descriptive analysis of functional data such as depth measurements, outlier detection, as well as unsupervised and supervised classification, (univariate, nonparametric) regression models with a functional covariate and functional analysis of variance.