# RcppArmadillo 0.2.2

**Thinking inside the box**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

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This release works well with the most recent
inline
release 0.3.5. One can now employ inlined R code as we generalized
how/which headers are included and how library / linking information is added
thanks a plugin mechanism. This is the first RcppArmadillo version to provide such
a plugin, We also updated the included Armadillo headers to its most recent release 0.9.10, added
some more operators and provide a utility function `RcppArmadillo:::CxxFlags()`
to provide include directory information on the fly.

An example of the direct inline approach for the `fastLm` function:

library(inline) library(RcppArmadillo) src <- ' Rcpp::NumericVector yr(ys); // creates Rcpp vector from SEXP Rcpp::NumericMatrix Xr(Xs); // creates Rcpp matrix from SEXP int n = Xr.nrow(), k = Xr.ncol(); arma::mat X(Xr.begin(), n, k, false); // reuses memory and avoids extra copy arma::colvec y(yr.begin(), yr.size(), false); arma::colvec coef = arma::solve(X, y); // fit model y ~ X arma::colvec res = y - X*coef; // residuals double s2 = std::inner_product(res.begin(), res.end(), res.begin(), double())/(n - k); // std.errors of coefficients arma::colvec std_err = arma::sqrt(s2 * arma::diagvec( arma::inv(arma::trans(X)*X) )); return Rcpp::List::create(Rcpp::Named("coefficients") = coef, Rcpp::Named("stderr") = std_err, Rcpp::Named("df") = n - k ); ' fun <- cxxfunction(signature(ys="numeric", Xs="numeric"), src, plugin="RcppArmadillo")

This creates a compiled function `fun` which, by using
Armadillo, regresses a vector `ys`
on a matrix `Xs` (just how the `fastLmPure()` function in the
package does) --- yet is constructed on the fly using `cxxfunction`
from
inline.

More information is on the RcppArmadillo page. Questions, comments etc should go to the rcpp-devel mailing list off the R-Forge page.

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