The Art of R Programming: A Tour of Statistical Software Design

Capa
No Starch Press, 11 de out. de 2011 - 400 páginas
R is the world's most popular language for developing statistical software: Archaeologists use it to track the spread of ancient civilizations, drug companies use it to discover which medications are safe and effective, and actuaries use it to assess financial risks and keep economies running smoothly.

The Art of R Programming takes you on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anonymous functions. No statistical knowledge is required, and your programming skills can range from hobbyist to pro.

Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to:
–Create artful graphs to visualize complex data sets and functions
–Write more efficient code using parallel R and vectorization
–Interface R with C/C++ and Python for increased speed or functionality
–Find new R packages for text analysis, image manipulation, and more
–Squash annoying bugs with advanced debugging techniques

Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.
 

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LibraryThing Review

Comentário do usuário  - nmarun - LibraryThing

This book IMHO is an excellent starting point for learning R. I'm finding it really useful for beginners like me to learn this new programming language. The book is comprehensive and well-illustrated ... Ler resenha completa

LibraryThing Review

Comentário do usuário  - nvenkataraman1 - LibraryThing

Outstanding introductory programming book for R programming. Covers a vast range of topics in sufficient depth for a beginner to get off the ground. Ler resenha completa

Conteúdo

Getting Started
1
Vectors
25
Matrices and Arrays
59
Lists
85
Data Frames
101
Factors and Tables
121
R Programming Structures
139
Doing Math and Simulations in R
189
String Manipulation
251
Graphics
261
Debugging
285
Performance Enhancement Speed and Memory
305
Interfacing R to Other Languages
323
Parallel R
333
Installing R
353
Installing and Using Packages
355

ObjectOriented Programming
207
InputOutput
231

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Sobre o autor (2011)

Norman Matloff is a professor of computer science (and was formerly a professor of statistics) at the University of California, Davis. His research interests include parallel processing and statistical regression, and he is the author of a number of widely-used Web tutorials on software development. He has written articles for the New York Times, the Washington Post, Forbes Magazine, and the Los Angeles Times, and is the co-author of The Art of Debugging (No Starch Press).

Informações bibliográficas