'Rcpp' Integration for 'GNU GSL' Vectors and Matrices

'Rcpp' integration for 'GNU GSL' vectors and matrices The 'GNU Scientific Library' (or 'GSL') is a collection of numerical routines for scientific computing. It is particularly useful for C and C++ programs as it provides a standard C interface to a wide range of mathematical routines. There are over 1000 functions in total with an extensive test suite. The 'RcppGSL' package provides an easy-to-use interface between 'GSL' data structures and R using concepts from 'Rcpp' which is itself a package that eases the interfaces between R and C++. This package also serves as a prime example of how to build a package that uses 'Rcpp' to connect to another third-party library. The 'autoconf' script, 'inline' plugin and example package can all be used as a stanza to write a similar package against another library.

This package uses Rcpp to connect the R system to the GNU GSL, a collection of numerical routines for scientific computing, particularly its vector and matrix classes.


Faster lm() for OLS regression

The fastLm() function included as file src/fastLm.cpp in the package:

#include <RcppGSL.h>
#include <gsl/gsl_multifit.h>
#include <cmath>
// [[Rcpp::export]]
Rcpp::List fastLm(const RcppGSL::Matrix &X, const RcppGSL::Vector &y) {
    int n = X.nrow(), k = X.ncol();
    double chisq;
    RcppGSL::Vector coef(k);                // to hold the coefficient vector 
    RcppGSL::Matrix cov(k,k);               // and the covariance matrix
    // the actual fit requires working memory we allocate and free
    gsl_multifit_linear_workspace *work = gsl_multifit_linear_alloc (n, k);
    gsl_multifit_linear (X, y, coef, cov, &chisq, work);
    gsl_multifit_linear_free (work);
    // assign diagonal to a vector, then take square roots to get std.error
    Rcpp::NumericVector std_err;
    std_err = gsl_matrix_diagonal(cov);  // need two step decl. and assignment
    std_err = Rcpp::sqrt(std_err);          // sqrt() is an Rcpp sugar function
    return Rcpp::List::create(Rcpp::Named("coefficients") = coef, 
                              Rcpp::Named("stderr")       = std_err,
                              Rcpp::Named("df.residual")  = n - k);

A simple column norm

This example comes from the complete example package included in RcppGSL and is from the file inst/examples/RcppGSLExample/src/colNorm.cpp

#include <RcppGSL.h>
#include <gsl/gsl_matrix.h>
#include <gsl/gsl_blas.h>
// [[Rcpp::export]]
Rcpp::NumericVector colNorm(const RcppGSL::Matrix & G) {
    int k = G.ncol();
    Rcpp::NumericVector n(k);           // to store results
    for (int j = 0; j < k; j++) {
        RcppGSL::VectorView colview = gsl_matrix_const_column (G, j);
        n[j] = gsl_blas_dnrm2(colview);
    return n;                           // return vector



On CRAN, here and on its package page.


Dirk Eddelbuettel and Romain Francois


GPL (>= 2)


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


0.3.9 by Dirk Eddelbuettel, 3 months ago

https://github.com/eddelbuettel/rcppgsl, https://dirk.eddelbuettel.com/code/rcpp.gsl.html

Report a bug at https://github.com/eddelbuettel/rcppgsl/issues

Browse source code at https://github.com/cran/RcppGSL

Authors: Dirk Eddelbuettel and Romain Francois

Documentation:   PDF Manual  

GPL (>= 2) license

Imports Rcpp, stats

Suggests tinytest

Linking to Rcpp

System requirements: GNU GSL

Imported by diseq.

Linked to by CLVTools, QF, RKHSMetaMod, RcppZiggurat, catSurv, coga, crandep, econetwork, fingerPro, flan, jSDM, libstableR, mashr, mixlink, mixture, mvabund, smam.

See at CRAN