Statistical Computing in C++ and R

C6650

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 specic 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.

Statistical Computing in C++ and R

Eubank

Kupresanin

Statistics

Statistical Computing

in C++ and R

Randall L. Eubank

Ana Kupresanin

The R Series

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Statistical Computing

in C++ and R

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Chapman & Hall/CRC

The R Series

John M. Chambers

Department of Statistics

Stanford University

Stanford, California, USA

Duncan Temple Lang

Department of Statistics

University of California, Davis

Davis, California, USA

Torsten Hothorn

Institut für Statistik

Ludwig-Maximilians-Universität

München, Germany

Hadley Wickham

Department of Statistics

Rice University

Houston, Texas, USA

Aims and Scope

This book series reects the recent rapid growth in the development and application of R, the

programming language and software environment for statistical computing and graphics. R is

now widely used in academic research, education, and industry. It is constantly growing, with

new versions of the core software released regularly and more than 2,600 packages available.

It is difcult for the documentation to keep pace with the expansion of the software, and this

vital book series provides a forum for the publication of books covering many aspects of the

development and application of R.

The scope of the series is wide, covering three main threads:

• Applications of R to specic disciplines such as biology, epidemiology, genetics,

engineering, nance, and the social sciences.

• Using R for the study of topics of statistical methodology, such as linear and mixed

modeling, time series, Bayesian methods, and missing data.

• The development of R, including programming, building packages, and graphics.

The books will appeal to programmers and developers of R software, as well as applied

statisticians and data analysts in many elds. The books will feature detailed worked

examples and R code fully integrated into the text, ensuring their usefulness to researchers,

practitioners and students.

Series Editors

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Randall L. Eubank

Arizona State University

Tempe, California, USA

Ana Kupresanin

Lawrence Livermore National Laboratory

Livermore, California, USA

The R Series

Statistical Computing

in C++ and R

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