OTHER PLACES OF INTEREST

Danny Flamberg's Blog

Danny has been marketing for a while, and his articles and work reflect great understanding of data driven marketing.

Eric Peterson the Demystifier

Eric gets metrics, analytics, interactive, and the real world. His advice is worth taking...

Geeking with Greg

Greg Linden created Amazon's recommendation system, so imagine what can write about...

Ned Batchelder's Blog

Ned just finds and writes interesting things. I don't know how he does it.

R at LoyaltyMatrix

Jim Porzak tells of his real-life use of R for marketing analysis.

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NAVIGATION

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(If you’ve found this via searching, you may enjoy the entire series of R articles, found via the navigation link on the right, R Statistical System. These are all in “somewhat random notes” style, but they’ve been helpful to me in the past. Feel free to ping me with updates or suggestions.)

?extract talks about how to pull out specific parts of a matrix/grid

Probably should move these to the R Wiki Links page

Besides all the fun stuff below, there is an R Wiki and the R Graph Gallery the wiki is really weak and needs all the love it can get while the Gallery is really eye-opening and could be one of the best things in the R Community (next to the R for SAS and SPSS Users book by Robert Muenchen). Additional graphing info can be seen at the RGraphExampleLibrary Package List

There is a shell of a book at Wikibooks, http://en.wikibooks.org/wiki/R_Programming and this could probably use some help as well.

**Search Engines Dedicated to R**

R-Seek has some nice features, including different tabs for different results types.

R MultiSearch gives 3 search boxes, one for Google, Swiki, and Rollyo, all aimed at R sites. BTW, this one searches Baron’s site (see below)

R Site Search by Jonathon Baron. Pretty good, but getting a bit long in the tooth. Includes most R documents, functions, and R-help mail archives including R-help, R-sig-geo, and R-sig-mixed-models messages.

http://www.r-ice.org/ was ok, but gone already…

**Impressive**

The Fantastic R for SAS and SPSS Users.

From Vanderbilt, R and S-Plus Packages, Functions, and Documentation including the very nice An Introduction to S and the Hmisc and Design Libraries by CF Alzola and FE Harrell (PDF).

Gmane has a collection of links to other lists, including

http://news.gmane.org/gmane.comp.lang.r.gui as well as the overall listing, http://news.gmane.org/index.php?prefix=gmane.comp.lang.r

In some ways, Nabble beats Gmane for ease of use. Check all of the Nabble Statistics Archive Lists including PSPP and R, and look at the combined R lists at http://www.nabble.com/R-f13819.html

Data Mining With Rattle and R Book gives both good stats stuff, and tells how to use the Rattle GUI which is a cool little tool. This is an entire book, but a bit hard to read page to page because of too many “splits” of content.

Data Mining with R: learning by case studies by Luís Torgo is an entire book on data mining with R, including code. Not updated since 2002.

**Good**

Quick-R is a good quick intro to R.

Using R for psychological research:A simple guide to an elegant package is a pretty nice start, pretty quick.

R code for graphics from the book R Graphics by Paul Murrell. In a nice gesture, he shows the graph with the code, which is very cool.

Producing Simple Graphs with R is a nice page for making graphs.

Handy list of commands to keep around: The R Reference Card by Tom Short and the rpad group. (Actually, this whole site http://rpad.googlecode.com/svn/Rpad_homepage/index.html has some interesting things, like docs with examples which run “in the browser” and other useful links). Other ref cards are linked at Baron’s page: http://finzi.psych.upenn.edu/

**Probably not a big deal**

R help for Statistics 371 gives some small tips, scripts. No biggie.

Applied Econ:e-Tutorial 2: A Brief Introduction to R also some small tips, scripts.

R/S-Plus links

**Still not sure what to do with**

http://www.maths.bris.ac.uk/~maman/computerstuff/Rhelp.html

http://www.nexusworkflow.com/ via http://www.r-project.org/useR-2006/Slides/DowlatyEtAl.pdf

http://www.statistik.tuwien.ac.at/public/dutt/ via http://www.r-project.org/useR-2006/Slides/Dutter.pdf

Slightly more advanced Notes on using R (PDF)

From the R Mailing List:

[R] Create a new var reflecting the order of subjects in existing var

Things I always forget about R now at Archive.org.

Programming in R last updated Jan 2007

http://faculty.washington.edu/tlumley/b514/R-fundamentals.pdf

and

http://faculty.washington.edu/tlumley/b514/lectures.html

Both by Tom Lumley, an R core developer/ The PDF is 208 pretty impressive pages.

Data Mining With Rattle and R: Open Source Desktop Survival Guide More good stuff from Togaware.

R by Example Some good little snippets, last updated 2005

Quick Tutorial in Time Series with R. The whole site is pretty good: http://www.stat.pitt.edu/stoffer/tsa2/index.html if you want to learn about Time Series analysis.

A Quick, Painless Tutorial on the R Statistical Package So, the quick and painless one is out of date, and the up to date one is really aimed at programmers, meaning it is neither quick nor painless.

From SPSS to R on the R Wiki.

R Cookbook Pretty impressive, so of course, it’s gone. He still has https://mywebspace.wisc.edu/neely/web/Site/CDE%20R%20Short%20Course.html a short course.

Supposedly, this textbook of statistics with R is pretty good.

http://www2.warwick.ac.uk/fac/sci/moac/degrees/modules/ch923/r_introduction/

R cheatsheet from 1998 I guess things don’t change all that much; most of this still works.

R software by Henrik Bengtsson

Programming in R is a very programmer oriented discussion, but pretty handy.

Using R for Psychological Research

SQLDF for R This clever little tool let’s you use SQL to manipulate data frames. Think of SAS’s Proc SQL. A somewhat similar project is sqlitedf SQLite Data Frames for R, which has not been updated since Dec 2007.

gsubfn is an R package used for string matching, substitution and parsing.

batchfiles Windows batchfiles for use with R Appears to be ways to start R adding proper paths, etc.

Rattle (the R Analytical Tool To Learn Easily) provides a simple and logical interface for data mining. and also at http://rattle.togaware.com/

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Rory Winston’s Blog, The Research Kitchen, has some great samples of really optimized R code. Good to learn from.

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Princeton Guide: http://libguides.princeton.edu/content.php?pid=27916&sid=456792

Ipsur: http://ipsur.org/

RDataMining: http://www.rdatamining.com/resources/onlinedocs

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Apropos of nothing, this is really cool: http://animation.yihui.name/dmml:k-nearest_neighbour_algorithm

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