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 ORCID iD [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_0.2.1.1.zip, r-release: sparseMVN_0.2.1.1.zip, r-oldrel: sparseMVN_0.2.1.1.zip
macOS binaries: r-release (arm64): sparseMVN_0.2.1.1.tgz, r-release (x86_64): sparseMVN_0.2.1.1.tgz, r-oldrel: sparseMVN_0.2.1.1.tgz
Old sources: sparseMVN archive

Reverse dependencies:

Reverse imports: ar.matrix, bgsmtr, disaggregation, netprioR, spsur

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