Introduction to R software

Published 10/30/2015 04:13:59 AM  |  Last update 10/30/2015 04:19:55 AM
Tags: R language, cloud computing, Statistics

R, by Ross Ihaka and Robert Gentleman- professors in statistics, is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories by John Chambers and colleagues. R can be considered as a different implementation of S because of some important differences. However, code written for S runs unaltered under R.

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. A number of R extensions, or packages, are from recent research works of statisticians, engineers and scientists in different areas. These extensions add advanced algorithms, colored and textured graphs and mining techniques to dig the data deeper. These then allow other researchers to do very intricate and complicated analyses without knowing the blood and guts of computing systems. “R is a real demonstration of the power of collaboration, and I don’t think you could construct something like this any other way,” Mr. Ihaka, one of R's co-creators said. R is available as Free Software under the terms of the Free Software Foundation's GNU General Public License in source code form. It compiles and runs on a wide variety of UNIX platforms and similar systems (including FreeBSD and Linux), Windows and MacOS. Using R software in data analysis helps saving much time and budget. However, R, based on Java VM, may have significant requirement on the system memory. A powerful computer with large amount of memory is ideal when using R to analyze large datasets.

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