Efficient R Programming
by Colin Gillespie, Robin Lovelace
Publisher: O'Reilly 2016
Number of pages: 150
Efficient R Programming is about increasing the amount of work you can do with R in a given amount of time. It's about both computational and programmer efficiency. This book is for anyone who uses R and who wants to make their use of R more reproducible, scalable, and faster.
Home page url
Download or read it online for free here:
by John Verzani - Chapman & Hall/CRC
A self-contained treatment of statistical topics and the intricacies of the R software. The book focuses on exploratory data analysis, includes chapters on simulation and linear models. It lays the foundation for further study and development using R.
by W. N. Venables, D. M. Smith - Network Theory
Comprehensive introduction to R, a software package for statistical computing and graphics. R supports a wide range of statistical techniques, and is easily extensible via user-defined functions, or using modules written in C, C++ or Fortran.
by Vincent Zoonekynd
Contents: Introduction to R; Programming in R; From Data to Graphics; Customizing graphics; Factorial methods; Clustering; Probability Distributions; Estimators and Statistical Tests; Regression; Other regressions; Regression Problems; etc.
by Roger D. Peng - Leanpub
This book teaches you to use R to effectively visualize and explore complex datasets. Exploratory data analysis is a key part of the data science process because it allows you to sharpen your question and refine your modeling strategies.