MultiRNG: Multivariate Pseudo-Random Number Generation

Pseudo-random number generation for 11 multivariate distributions: Normal, t, Uniform, Bernoulli, Hypergeometric, Beta (Dirichlet), Multinomial, Dirichlet-Multinomial, Laplace, Wishart, and Inverted Wishart. The details of the method are explained in Demirtas (2004) <doi:10.22237/jmasm/1099268340>.

Version:	1.2.4
Published:	2021-03-05
Author:	Hakan Demirtas, Rawan Allozi, Ran Gao
Maintainer:	Ran Gao <rgao8 at uic.edu>
License:	GPL-2 | GPL-3
NeedsCompilation:	no
In views:	Distributions
CRAN checks:	MultiRNG results

Documentation:

Reference manual:

MultiRNG.pdf

Downloads:

Package source:	MultiRNG_1.2.4.tar.gz
Windows binaries:	r-devel: MultiRNG_1.2.4.zip, r-release: MultiRNG_1.2.4.zip, r-oldrel: MultiRNG_1.2.4.zip
macOS binaries:	r-release (arm64): MultiRNG_1.2.4.tgz, r-oldrel (arm64): MultiRNG_1.2.4.tgz, r-release (x86_64): MultiRNG_1.2.4.tgz, r-oldrel (x86_64): MultiRNG_1.2.4.tgz
Old sources:	MultiRNG archive

Reverse dependencies:

Reverse imports:	PDFEstimator
Reverse suggests:	phenology

Linking:

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