Sparse matrix use cases (resolving declaration issues)

[bgoodri]

@Daniel_Simpson

csr_matrix_times_vector(…, x);

is slower than an abacus. This might be faster:

Sparse double matrix times vector of vars

Here is an improved version of the C++ code #include <Rcpp.h> #include <RcppEigen.h> // [[Rcpp::depends(RcppEigen)]] // [[Rcpp::export]] Eigen::VectorXd smv(int rows, int cols, const std::vector<double>& Values, const std::vector<int>& InnerIndices, const std::vector<int>& OuterStarts, const Eigen::VectorXd& beta) { Eigen::Map<const Eigen::SparseMatrix<double,Eigen::RowMajor> > sm(rows, cols, Values.size(), &OuterStarts[0], &InnerIndices[0], &Values[0]); // To do d…