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Eigen is a C++ template library for linear algebra:matrices, vectors, numerical solvers and related algorithms. It supports dense and sparsematrices on integer, floating point and complex numbers, decompositions of such matrices,and solutions of linear systems. Its performance on many algorithms is comparable withsome of the best implementations based onLapack and level-3BLAS.

RcppEigen provides an interface from R to and fromEigen byusing the facilities offered by theRcpppackage for seamless R and C++ integration.

A few examples are over at theRcpp Gallery. A simple one is

#include<RcppEigen.h>// [[Rcpp::depends(RcppEigen)]]using Eigen::Map;// 'maps' rather than copiesusing Eigen::MatrixXd;// variable size matrix, double precisionusing Eigen::VectorXd;// variable size vector, double precisionusing Eigen::SelfAdjointEigenSolver;// one of the eigenvalue solvers// [[Rcpp::export]]VectorXdgetEigenValues(Map<MatrixXd> M) {    SelfAdjointEigenSolver<MatrixXd>es(M);return es.eigenvalues();}

which can be turned into a function callable from R via a simple

sourceCpp("eigenExample.cpp")

due to the two Rcpp directives to use headers from the RcppEigen package, and to exportthegetEigenValues() function -- but readthe fullpost for details.

The package is mature and under active development, following theEigen release cycle.

The package contains a pdf vignette which is a pre-print of thepaper byBates and Eddelbuettel in JSS (2013, v52i05).

Douglas Bates, Dirk Eddelbuettel, Romain Francois, and Yixuan Qiu

GPL (>= 2)