Introduction To R

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Introduction To R

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Introduction To R

  1. 1. Introduction to<br />The Dataminingtools.net Team<br />
  2. 2. What is R ?<br />R is a programming language and software environment for statistical computing and graphics. It is an implementation of the S programming language with lexical scoping semantics inspired by Scheme. R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand.<br />
  3. 3. History<br />Version 0.16 – This is the last alpha version developed . Much of the basic functionality from the &quot;White Book&quot; was implemented. The mailing lists commenced on April 1, 1997.<br />Version 0.49 – April 23, 1997 – This is the oldest available source release, and compiles on a limited number of Unix-like platforms. CRAN is started on this date, with 3 mirrors that initially hosted 12 packages. Alpha versions of R for Microsoft Windows and Mac OS are made available shortly after this version.<br />Version 0.60 – December 5, 1997 – R becomes an official part of the GNU Project. The code is hosted and maintained on CVS.<br />Version 1.0.0 – February 29, 2000 – Considered by its developers stable enough for production use [11].<br />Version 1.4.0 – S4 methods are introduced and the first version for Mac OS X is made available soon after.<br />Version 2.0.0 – Introduced lazy loading, which enables fast loading of data with minimal expense of system memory.<br />Version 2.1.0 – Support for UTF-8 encoding, and the beginnings of internationalization and localization for different languages.<br />Version 2.9.0 – Package &apos;Matrix&apos; is now a recommended package contained in the basic R distribution.<br />-Source: http://en.wikipedia.org/wiki/R_(programming_language)<br />
  4. 4. Features<br />It&apos;s free! You don’t have to shell out any money for using R!<br />R is part of the GNU project. Its source code is freely available under the GNU General Public License<br />It is cross-platform and its packages are available for Windows, Mac OS and Linux.<br />
  5. 5. Features<br />Unparalleled platform for programming new statistical methods in an easy and straightforward manner.<br />Supports advanced statistical routines hardly available in other packages.<br />Amazing graphics capabilities.<br />
  6. 6. Features<br />Supported Statistical features:<br />linear modeling<br />nonlinear modeling<br />classical statistical tests<br />time-series analysis<br />Classification<br />clustering<br />
  7. 7. Features<br />R produces publication-quality graphs which can include mathematical symbols. 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 hard copy.<br />
  8. 8. Obtaining R<br />R is available for Linux, Mac OS X, and Windows (95 or later) platforms. The software can be downloaded from one of the  Comprehensive R Archive Network (CRAN) mirror sites.<br />

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