sparseMVN: Multivariate Normal Functions for Sparse Covariance and Precision Matrices

Computes multivariate normal (MVN) densities, and samples from MVN distributions, when the covariance or precision matrix is sparse.

Version:	0.2.2
Depends:	R (≥ 3.4.0)
Imports:	Matrix (≥ 1.3), methods
Suggests:	dplyr (≥ 1.0), tidyr (≥ 1.1), ggplot2 (≥ 3.3), forcats (≥ 0.5), mvtnorm (≥ 1.0.6) , knitr, bookdown, kableExtra, testthat, scales, trustOptim (≥ 0.8.5)
Published:	2021-10-25
Author:	Michael Braun [aut, cre, cph]
Maintainer:	Michael Braun <braunm at smu.edu>
BugReports:	https://github.com/braunm/sparseMVN/issues/
License:	MPL (≥ 2.0)
URL:	https://braunm.github.io/sparseMVN/, https://github.com/braunm/sparseMVN/
NeedsCompilation:	no
Materials:	NEWS
In views:	Distributions
CRAN checks:	sparseMVN results

Documentation:

Reference manual:	sparseMVN.pdf
Vignettes:	The sparseMVN package

Downloads:

Package source:	sparseMVN_0.2.2.tar.gz
Windows binaries:	r-devel: sparseMVN_0.2.2.zip, r-release: sparseMVN_0.2.2.zip, r-oldrel: sparseMVN_0.2.2.zip
macOS binaries:	r-release (arm64): sparseMVN_0.2.2.tgz, r-oldrel (arm64): sparseMVN_0.2.2.tgz, r-release (x86_64): sparseMVN_0.2.2.tgz, r-oldrel (x86_64): sparseMVN_0.2.2.tgz
Old sources:	sparseMVN archive

Reverse dependencies:

Reverse imports:

ar.matrix, bgsmtr, disaggregation, netprioR, spsur

Linking:

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