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020 _a9781461468684
_9978-1-4614-6868-4
024 7 _a10.1007/978-1-4614-6868-4
_2doi
050 4 _aQA276-280
072 7 _aUFM
_2bicssc
072 7 _aCOM077000
_2bisacsh
082 0 4 _a519.5
_223
100 1 _aEddelbuettel, Dirk.
_eauthor.
245 1 0 _aSeamless R and C++ Integration with Rcpp
_h[electronic resource] /
_cby Dirk Eddelbuettel.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2013.
300 _aXXVIII, 220 p. 7 illus., 4 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aUse R! ;
_v64
505 0 _aPreface -- 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 .
520 _aRcpp 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! — Søren Højsgaard, Department of Mathematical Sciences, Aalborg University, Denmark Seamless R and C ++ Integration with Rcpp provides the first comprehensive introduction to Rcpp, which 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.
650 0 _aStatistics.
650 0 _aMathematical statistics.
650 1 4 _aStatistics.
650 2 4 _aStatistics and Computing/Statistics Programs.
650 2 4 _aStatistical Theory and Methods.
650 2 4 _aProbability and Statistics in Computer Science.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781461468677
830 0 _aUse R! ;
_v64
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-6868-4
912 _aZDB-2-SMA
942 _2Dewey Decimal Classification
_ceBooks
999 _c44743
_d44743