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
C6650_Cover.indd 1 10/26/11 9:31 AM
Statistical Computing
in C++ and R
C6650_FM.indd 1 10/27/11 4:15 PM
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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