R, where should I start?

March 17, 2013

(This article was first published on Blend it like a Bayesian!, and kindly contributed to R-bloggers)

This is a dynamic post which I will continue to update whenever I find something new. Hope you will find the following links useful.

Online Courses for Learning the R language

  1. Try R from Code School

e-Books for Learning the R Language

  1. R for Beginners by Emmanuel Paradis
  2. R Graphics by Paul Murrel
  3. ggplot2 (official documentation)

Online Courses for Data Mining with R

  1. Data Analysis by Jeff Leek (Coursera)
  2. Computing for Data Analysis by Roger Peng (Coursera)
  3. Data and Computing Fundamentals by Danny Kaplan and Libby Shoop (Macalester College)

e-Books for Data Mining with R

R Tutorials

  1. Twotorials by Anthony Damico (learning new tricks from short 2-min videos)
  2. Revolution Analytics Free Webinars
  3. ggplot2 Graphics Cheat Sheet
  4. 10 tips for making your R graphics look their best
  5. Making Maps with R
  6. Compiling R 3.0.1 with MKL support

Interesting Blogs

Useful R Packages

  1. Ten R packages I wish I knew about earlier (Before you do anything, read this blog post first!!)
  2. caret (short for Classification And REgression Training) for a simple way to train and fine-tune model using different algorithms
  3. ff and bigmemory – two packages to solve memory issues with big datasets
  4. quantmod for financial modelling
  5. foreach and doSNOW for parallel computing in R

Interactive Development Environment

  1. RStudio – a really nice IDE for R
  2. RStudio Server Amazon Machine Image by Louis Aslett (Wanna run RStudio on Amazon EC2? Try this!)

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Mango solutions

RStudio homepage

Zero Inflated Models and Generalized Linear Mixed Models with R

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CRC R books series

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