Multivariate Normal Functions for Sparse Covariate and Precision Matrices

MVN functions for sparse covariance and precision matrices.

Details

Computes multivariate normal (MVN) densities, and samples from MVN distributions, when either the covariance or precision matrix is stored as a sparse Matrix (a dsCMatrix object, as defined in the Matrix package. The user can provide the precision matrix directly, rather than convert it to a covariance via matrix inversion.

See also

Useful links:

• https://braunm.github.io/sparseMVN/

• https://github.com/braunm/sparseMVN/

• Report bugs at https://github.com/braunm/sparseMVN/issues/

Author

Maintainer: Michael Braun braunm@smu.edu (ORCID) [copyright holder]