Software for Data Analysis: Programming with R (Statistics and Computing)
By John M. Chambers
Publisher: Springer
Number Of Pages: 512
Publication Date: 2008-07-18
ISBN-10 / ASIN: 0387759352
ISBN-13 / EAN: 9780387759357
Binding: Hardcover
Number Of Pages: 512
Publication Date: 2008-07-18
ISBN-10 / ASIN: 0387759352
ISBN-13 / EAN: 9780387759357
Binding: Hardcover
Springer介绍:http://www.springer.com/statistics/computational/book/978-0-387-75935-7
About this book
The only advanced programming book on R
Begins with simple interactive use and progresses by gradual stages
Written by the award winning author of the S language from which R evolved
John Chambers has been the principal designer of the S language since its beginning, and in 1999 received the ACM System Software award for S, the only statistical software to receive this award. He is author or coauthor of the landmark books on S.
Now he turns to R, the enormously successful open-source system based on the S language. R's international support and the thousands of packages and other contributions have made it the standard for statistical computing in research and teaching.
This book guides the reader through programming with R, beginning with simple interactive use and progressing by gradual stages, starting with simple functions. More advanced programming techniques can be added as needed, allowing users to grow into software contributors, benefiting their careers and the community. R packages provide a powerful mechanism for contributions to be organized and communicated.
The techniques covered include such modern programming enhancements as classes and methods, namespaces, and interfaces to spreadsheets or data bases, as well as computations for data visualization, numerical methods, and the use of text data.
Written for:
Researchers, practitioners
Keywords:
DATA ANALYSIS
DATA VISUALIZATION
PROGRAMMING
STATISTICAL COMPUTING
Table of contents
Computing with data.- Using R.- Programming: The basics.- Objects.- Data.- Data visualiation and graphics.- Computations: The basics.- Computing with text.- How R works.- R packages.- New classes.- Methods and generic functions.- Programming for users.- Designing and training software.- C and Fortran.- Interfaces with other systems.- Programming models.
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