Package

r-fastmatrix

Description

Fast Computation of some Matrices Useful in Statistics. Small set of
functions to fast computation of some matrices and operations useful in
statistics and econometrics. Currently, there are functions for
efficient computation of duplication, commutation and symmetrizer
matrices with minimal storage requirements. Some commonly used matrix
decompositions (LU and LDL), basic matrix operations (for instance,
Hadamard, Kronecker products and the Sherman-Morrison formula) and
iterative solvers for linear systems are also available. In addition,
the package includes a number of common statistical procedures such as
the sweep operator, weighted mean and covariance matrix using an online
algorithm, linear regression (using Cholesky, QR, SVD, sweep operator
and conjugate gradients methods), ridge regression (with optimal
selection of the ridge parameter considering the GCV procedure),
functions to compute the multivariate skewness, kurtosis, Mahalanobis
distance (checking the positive defineteness) and the Wilson-Hilferty
transformation of chi squared variables. Furthermore, the package
provides interfaces to C code callable by another C code from other R
packages.

Note