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R should work well on any reasonably recent computer. Find the appropriate page for your operating system, and read and follow the installation instructions. To do so, go to and find a mirror site that is geographically somewhat near you. You can download precompiled binaries for most major platforms from any CRAN mirror. You can get the source code and compile it yourself, but you may prefer at this point to download and install a precompiled version. The main source for R is the Comprehensive R Archive Network (CRAN). Before learning about these, however, you should learn a little about R itself. At present, the best of these appears to be RStudio. There are a number of graphical front-ends for R. Originally a research project in statistical computing (Ihaka and Gentleman 1996), it is now managed by a development team that includes a number of well-regarded statisticians, and is widely used by statistical researchers and working scientists as a platform for making new methods available to users.
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R is an open source software project, available for free download (R Core Team 2014a). extensive help and documentation facilities.a modular and extensible structure that supports a vast array of optional add-on packages, and.graphics functions for visualizing data and model output,.powerful numerical analysis tools for linear algebra, differential equations, and stochastics,.an extensive set of functions for classical and modern statistical data analysis and modeling,.a programming language called S, developed by John Chambers at Bell Labs, that implements the idea of programming with data (Chambers 1998),.R is a computing environment that combines
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Comments, suggestions, criticism, corrections are most welcome. The source code for this document is here. Please share and remix noncommercially, mentioning its origin. Licensed under the Creative Commons Attribution-NonCommercial license. 14.6 sapply with expected result: vapply.