Preface.- Introduction.- A Gentle Introduction to Rcpp.- Tools and Setup.- Core Data Types.- Data Structures: Part One.- Data Structures: Part Two.- Advanced Topics.- Using Rcpp in your package.- Extending Rcpp.- Modules.- Sugar.- Applications.- RInside.- RcppArmadillo.- RcppGSL.- RcppEigen Appendix.- C++ for R programmers.- Indices.- References.
Über den Autor
Dirk Eddelbuettel has been a contributor to CRAN for over a decade and maintains around twenty packages. He is the Debian/Ubuntu maintainer for R and other quantitative software, edits the CRAN Task Views for Finance and High-Performance Computing, is a co-founder of the annual R/Finance conference, and an editor of the Journal of Statistical Software. He holds a Ph.D. in Mathematical Economics from EHESS (Paris), and works in Chicago as a Senior Quantitative Analyst.
Preface.- Introduction.- A Gentle Introduction to Rcpp.- Tools and Setup.- Core Data Types.- Data Structures: Part One.- Data Structures: Part Two.- Advanced Topics.- Using Rcpp in your package.- Extending Rcpp.- Modules.- Sugar.- Applications.- RInside.- RcppArmadillo.- RcppGSL.- RcppEigen Appendix.- C++ for R programmers.- Indices.- References¿.
Rcpp is the glue that binds the power and versatility of R with the speed and efficiency of C++. With Rcpp, the transfer of data between R and C++ is nearly seamless, and high-performance statistical computing is finally accessible to most R users. Rcpp should be part of every statistician's toolbox. -- Michael Braun, MIT Sloan School of Management
"Seamless R and C++ integration with Rcpp" is simply a wonderful book. For anyone who uses C/C++ and R, it is an indispensable resource. The writing is outstanding. A huge bonus is the section on applications. This section covers the matrix packages Armadillo and Eigen and the GNU Scientific Library as well as RInside which enables you to use R inside C++. These applications are what most of us need to know to really do scientific programming with R and C++. I love this book. -- Robert McCulloch, University of Chicago Booth School of Business
Rcpp is now considered an essential package for anybody doing serious computational research using R. Dirk's book is an excellent companion and takes the reader from a gentle introduction to more advanced applications via numerous examples and efficiency enhancing gems. The book is packed with all you might have ever wanted to know about Rcpp, its cousins (RcppArmadillo, RcppEigen .etc.), modules, package development and sugar. Overall, this book is a must-have on your shelf. -- Sanjog Misra, UCLA Anderson School of Management
The Rcpp package represents a major leap forward for scientific computations with R. With very few lines of C++ code, one has R's data structures readily at hand for further computations in C++. Hence, high-level numerical programming can be made in C++ almost as easily as in R, but often with a substantial speed gain. Dirk is a crucial person in these developments, and his book takes the reader from the
Illustrates a range of statistical computations in R using the Rcpp package
Provides a general introduction to extending R with C++ code
Features an appendix for R users new to the C++ programming language
Rcpp packages are presented in the context of useful application case studies