Abstract
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 Francois 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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