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: 0.2.1.1
Depends: R (≥ 3.4.0)
Imports: Matrix (≥ 1.2.12), methods
Suggests: mvtnorm (≥ 1.0.6), plyr, knitr, testthat, dplyr (≥ 0.5.0), scales, reshape2, trustOptim (≥ 0.8.5), xtable (≥ 1.8), ggplot2 (≥ 2.2.1), tidyr (≥ 0.6.1)
Published: 2018-03-26
Author: Michael Braun [aut, cre, cph]
Maintainer: Michael Braun <braunm at smu.edu>
License: MPL (≥ 2.0)
URL: http://www.smu.edu/Cox/Departments/FacultyDirectory/BraunMichael
NeedsCompilation: no
Materials: NEWS
In views: Distributions
CRAN checks: sparseMVN results

Downloads:

Reference manual: sparseMVN.pdf
Vignettes: Using sparseMVN
Package source: sparseMVN_0.2.1.1.tar.gz
Windows binaries: r-prerel: sparseMVN_0.2.1.1.zip, r-release: sparseMVN_0.2.1.1.zip, r-oldrel: sparseMVN_0.2.0.zip
OS X binaries: r-prerel: sparseMVN_0.2.1.1.tgz, r-release: sparseMVN_0.2.1.1.tgz
Old sources: sparseMVN archive

Reverse dependencies:

Reverse imports: bgsmtr
Reverse suggests: bayesGDS, loggle

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