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  • 标题:Fast and Elegant Numerical Linear Algebra Using the RcppEigen Package
  • 本地全文:下载
  • 作者:Douglas Bates ; Dirk Eddelbuettel
  • 期刊名称:Journal of Statistical Software
  • 印刷版ISSN:1548-7660
  • 电子版ISSN:1548-7660
  • 出版年度:2013
  • 卷号:52
  • 期号:1
  • 页码:1-24
  • 语种:English
  • 出版社:University of California, Los Angeles
  • 摘要:The RcppEigen package provides access from R (R Core Team 2012a) to the Eigen (Guennebaud, Jacob, and others 2012) C++ template library for numerical linear algebra. Rcpp (Eddelbuettel and François 2011, 2012) classes and specializations of the C++ templated functions as and wrap from Rcpp provide the "glue" for passing objects from R to C++ and back. Several introductory examples are presented. This is followed by an in-depth discussion of various available approaches for solving least-squares problems, including rank-revealing methods, concluding with an empirical run-time comparison. Last but not least, sparse matrix methods are discussed.
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