Statistical Computing in C++ and R

Randall L. Eubank

ISBN 10: 1420066501 / ISBN 13: 9781420066500

Published by CRC Press, 2011

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - Parallel processing can be ideally suited for the solving of more complex problems in statistical computing. This book discusses code development in C++ and R, before going beyond to look at the valuable use of these two languages in unison. It covers linear equation solution with regression and linear models motivation, optimization with maximum likelihood and nonlinear least squares motivation, and random number generation. While the text does require a working knowledge of both the basic concepts in statistics and experience in programming, it does not require knowledge specific to C++ or R.

Seller Inventory # 9781420066500

Bibliographic Details

• Title: Statistical Computing in C++ and R
• Publisher: CRC Press
• Publication Date: 2011
• Language: English
• ISBN 10: 1420066501
• ISBN 13: 9781420066500
• Binding: Buch
• Condition: Neu
• Dimensions: 260W x 183H x 34D millimeters 260 millimeters width by 183 millimeters height by 34 millimeters depth
• Weight: 1231 grams

About this title

Synopsis

With the advancement of statistical methodology inextricably linked to the use of computers, new methodological ideas must be translated into usable code and then numerically evaluated relative to competing procedures. In response to this, Statistical Computing in C++ and R concentrates on the writing of code rather than the development and study of numerical algorithms per se. The book discusses code development in C++ and R and the use of these symbiotic languages in unison. It emphasizes that each offers distinct features that, when used in tandem, can take code writing beyond what can be obtained from either language alone.

The text begins with some basics of object-oriented languages, followed by a "boot-camp" on the use of C++ and R. The authors then discuss code development for the solution of specific computational problems that are relevant to statistics including optimization, numerical linear algebra, and random number generation. Later chapters introduce abstract data structures (ADTs) and parallel computing concepts. The appendices cover R and UNIX Shell programming.

Features

• Includes numerous student exercises ranging from elementary to challenging
• Integrates both C++ and R for the solution of statistical computing problems
• Uses C++ code in R and R functions in C++ programs
• Provides downloadable programs, available from the authors’ website

The translation of a mathematical problem into its computational analog (or analogs) is a skill that must be learned, like any other, by actively solving relevant problems. The text reveals the basic principles of algorithmic thinking essential to the modern statistician as well as the fundamental skill of communicating with a computer through the use of the computer languages C++ and R. The book lays the foundation for original code development in a research environment.

About the Author

Arizona State University, Tempe, USA