Seamless R and C++ Integration with Rcpp 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024


Seamless R and C++ Integration with Rcpp

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Dirk Eddelbuettel 作者
Springer
譯者
2013-6-4 出版日期
248 頁數
GBP 47.99 價格
Paperback
叢書系列
9781461468677 圖書編碼

Seamless R and C++ Integration with Rcpp 在線電子書 圖書標籤: R  C++  數據分析  統計  Statistics  Mathematics  Finance  編程   


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Seamless R and C++ Integration with Rcpp 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Seamless R and C++ Integration with Rcpp 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Seamless R and C++ Integration with Rcpp 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024



Seamless R and C++ Integration with Rcpp 在線電子書 用戶評價

評分

我覺得底層機製沒有講得很清楚,雖然各個部分講得還比較細,但是它們是如何配閤運行的還是有點難懂。強烈建議先讀《Advanced R》的 "Rcpp" 和 "R’s C interface" 兩章。

評分

我覺得底層機製沒有講得很清楚,雖然各個部分講得還比較細,但是它們是如何配閤運行的還是有點難懂。強烈建議先讀《Advanced R》的 "Rcpp" 和 "R’s C interface" 兩章。

評分

即使會C++,也建議先看看最後一章Appendix A C++ for R Programmers,瞭解C++很多專業名詞,對閱讀本書有益,我是從頭看瞭一遍,感覺還要再看,如果想用C++編寫R包的話,這本書估計躲不過瞭。

評分

即使會C++,也建議先看看最後一章Appendix A C++ for R Programmers,瞭解C++很多專業名詞,對閱讀本書有益,我是從頭看瞭一遍,感覺還要再看,如果想用C++編寫R包的話,這本書估計躲不過瞭。

評分

即使會C++,也建議先看看最後一章Appendix A C++ for R Programmers,瞭解C++很多專業名詞,對閱讀本書有益,我是從頭看瞭一遍,感覺還要再看,如果想用C++編寫R包的話,這本書估計躲不過瞭。

Seamless R and C++ Integration with Rcpp 在線電子書 著者簡介


Seamless R and C++ Integration with Rcpp 在線電子書 著者簡介


Seamless R and C++ Integration with Rcpp 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Seamless R and C++ Integration with Rcpp 在線電子書 圖書描述

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 first fragile steps on to using the full Rcpp machinery. A very recommended book! -- Soren Hojsgaard, Department of Mathematical Sciences, Aalborg University, Denmark "Seamless R and C ++ Integration with Rcpp" provides the first comprehensive introduction to Rcpp. Rcpp has become the most widely-used language extension for R, and is deployed by over one-hundred different CRAN and BioConductor packages. Rcpp permits users to pass scalars, vectors, matrices, list or entire R objects back and forth between R and C++ with ease. This brings the depth of the R analysis framework together with the power, speed, and efficiency of C++. 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.

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