User:Timothee Flutre/Notebook/Postdoc/2011/11/07: Difference between revisions
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|style="background-color: #EEE"|[[Image:owwnotebook_icon.png|128px]]<span style="font-size:22px;"> Project name</span> | |style="background-color: #EEE"|[[Image:owwnotebook_icon.png|128px]]<span style="font-size:22px;"> Project name</span> | ||
|style="background-color: #F2F2F2" align="center"| | |style="background-color: #F2F2F2" align="center"|[[File:Report.png|frameless|link={{#sub:{{FULLPAGENAME}}|0|-11}}]][[{{#sub:{{FULLPAGENAME}}|0|-11}}|Main project page]]<br />{{#if:{{#lnpreventry:{{FULLPAGENAME}}}}|[[File:Resultset_previous.png|frameless|link={{#lnpreventry:{{FULLPAGENAME}}}}]][[{{#lnpreventry:{{FULLPAGENAME}}}}{{!}}Previous entry]] }}{{#if:{{#lnnextentry:{{FULLPAGENAME}}}}|[[{{#lnnextentry:{{FULLPAGENAME}}}}{{!}}Next entry]][[File:Resultset_next.png|frameless|link={{#lnnextentry:{{FULLPAGENAME}}}}]]}} | ||
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== | ==About R== | ||
* '''Motivation''': when analyzing data for any research project, it's essential to be able to quickly clean the raw data, transform them, plot intermediary results, calculate summary statistics, try various more-or-less sophisticated models, etc. This must be easily doable with small as well as large data sets, interactively or not. Several tools exist to fill exactly this need, and [http://en.wikipedia.org/wiki/R_%28programming_language%29 R] is only one of them, but I especially recommend it because it is build by statisticians (this means that the implemented models are numerous and state-of-the-art). Moreover, it's [http://cran.r-project.org/sources.html open-source] (and even [http://www.r-project.org/about.html free software]), platform-independent, full of [http://cran.r-project.org/web/packages/available_packages_by_name.html packages], with [http://cran.r-project.org/web/views/ well-documented] resources, etc, so give it a try! | |||
* '''Documentation''': | |||
** try it [https://www.codeschool.com/courses/try-r online] | |||
** learn how to use it with [http://swirlstats.com/ swirl] | |||
** official introductory [http://cran.r-project.org/doc/manuals/R-intro.html manual] | |||
** well-organized [http://www.statmethods.net/ how-to] | |||
** condensed [http://cran.r-project.org/doc/contrib/Baggott-refcard-v2.pdf reference card] | |||
** [http://grunwaldlab.github.io/Reproducible-science-in-R/index.html tutorial] on reproducible analysis with R | |||
** freely-available [http://adv-r.had.co.nz/ book] for advanced usage | |||
** [http://www.r-bloggers.com/ aggregator] of R blogs | |||
** [http://rpubs.com/ publishing platform] of R documents | |||
** [http://gallery.rcpp.org/ gallery] of examples extending R with C++ via [http://www.rcpp.org/ Rcpp] | |||
** compatible with [http://ess.r-project.org/ ESS] ([https://openwetware.org/wiki/User:Timothee_Flutre/Notebook/Postdoc/2012/07/25 Emacs] mode), besides other IDEs such as [http://www.rstudio.com/ Rstudio] | |||
** but R language specifications are unconventional ([https://github.com/tdsmith/aRrgh aRgh], John Cook's [http://www.johndcook.com/R_language_for_programmers.html doc], [http://www.burns-stat.com/pages/Tutor/R_inferno.pdf R Inferno]) | |||
* | * '''Tips''': | ||
** [http://menugget.blogspot.de/2013/01/my-template-for-controlling-publication.html procedure] for publication-quality plots | |||
** [https://sites.google.com/site/rosselldavid/home/tips tutorial] to debug within Emacs some C/C++ code called by R | |||
** make your own R package: [https://github.com/jtleek/rpackages policy] from Jeff Leek, [http://r-pkgs.had.co.nz/ book] from Hadley Wickham, [http://projecttemplate.net/ ProjectTemplate] | |||
** R [http://google-styleguide.googlecode.com/svn/trunk/Rguide.xml style guide] from Google | |||
** [http://cran.r-project.org/bin/linux/ubuntu/ upgrade] R on Ubuntu | |||
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Latest revision as of 21:05, 26 September 2017
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