# RcppGSL v0.3.1

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## '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 such as special functions, permutations, combinations, fast fourier transforms, eigensystems, random numbers, quadrature, random distributions, quasi-random sequences, Monte Carlo integration, N-tuples, differential equations, simulated annealing, numerical differentiation, interpolation, series acceleration, Chebyshev approximations, root-finding, discrete Hankel transforms physical constants, basis splines and wavelets. 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.

## RcppGSL

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.

### Examples

#### 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
}


### Availabililty

On CRAN, here and on its package page.

### Authors

Dirk Eddelbuettel and Romain Francois

GPL (>= 2)

## Functions in RcppGSL

 Name Description RcppGSL-package Glue between Rcpp and the GNU GSL fastLm Bare-bones linear model fitting function LdFlags Provide RcppGSL Compiler and Linker Flags No Results!