Package: tmvtnorm 1.7

tmvtnorm: Truncated Multivariate Normal and Student t Distribution

Random number generation for the truncated multivariate normal and Student t distribution. Computes probabilities, quantiles and densities, including one-dimensional and bivariate marginal densities. Computes first and second moments (i.e. mean and covariance matrix) for the double-truncated multinormal case.

Authors:Stefan Wilhelm [aut, cre], Manjunath B G [aut]

tmvtnorm_1.7.tar.gz
tmvtnorm_1.7.zip(r-4.7)tmvtnorm_1.7.zip(r-4.6)tmvtnorm_1.7.zip(r-4.5)
tmvtnorm_1.7.tgz(r-4.6-x86_64)tmvtnorm_1.7.tgz(r-4.6-arm64)tmvtnorm_1.7.tgz(r-4.5-x86_64)tmvtnorm_1.7.tgz(r-4.5-arm64)
tmvtnorm_1.7.tar.gz(r-4.7-arm64)tmvtnorm_1.7.tar.gz(r-4.7-x86_64)tmvtnorm_1.7.tar.gz(r-4.6-arm64)tmvtnorm_1.7.tar.gz(r-4.6-x86_64)
tmvtnorm_1.7.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
tmvtnorm/json (API)

# Install 'tmvtnorm' in R:

install.packages('tmvtnorm', repos = c('https://stefanwilhelm.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/stefanwilhelm/tmvtnorm/issues

Uses libs:

openblas– Optimized BLAS
fortran– Runtime library for GNU Fortran applications

On CRAN:

openblas fortran

9.81 score 2 stars 66 packages 888 scripts 9.1k downloads 4 mentions 16 exports 6 dependencies

Last updated from:8d2ccb11b1. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	165
linux-devel-x86_64	OK	180
source / vignettes	OK	223
linux-release-arm64	OK	180
linux-release-x86_64	OK	150
macos-release-arm64	OK	244
macos-release-x86_64	OK	320
macos-oldrel-arm64	OK	160
macos-oldrel-x86_64	OK	354
windows-devel	OK	107
windows-release	OK	97
windows-oldrel	OK	146
wasm-release	OK	103

Exports:dtmvnorm dtmvnorm.marginal dtmvnorm.marginal2 dtmvt gmm.tmvnorm mle.tmvnorm mtmvnorm ptmvnorm ptmvnorm.marginal ptmvt ptmvt.marginal qtmvnorm.marginal rtmvnorm rtmvnorm.sparseMatrix rtmvnorm2 rtmvt

Dependencies:gmm lattice Matrix mvtnorm sandwich zoo

A short description of the Gibbs Sampler

Gibbs Sampler with convariance matrix | Gibbs Sampler with precision matrix H | Gibbs Sampler for linear constraints

Rendered fromGibbsSampler.Rnwusingutils::Sweave

Last update: 2022-03-21
Started: 2016-12-04

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
One-dimensional marginal density functions from a Truncated Multivariate Normal distribution	dtmvnorm.marginal
Bivariate marginal density functions from a Truncated Multivariate Normal distribution	dtmvnorm.marginal2
Truncated Multivariate Student t Density	dtmvt
GMM Estimation for the Truncated Multivariate Normal Distribution	gmm.tmvnorm
Maximum Likelihood Estimation for the Truncated Multivariate Normal Distribution	mle.tmvnorm
Computation of Mean Vector and Covariance Matrix For Truncated Multivariate Normal Distribution	moments mtmvnorm
Truncated Multivariate Normal Distribution	ptmvnorm
Truncated Multivariate Student t Distribution	ptmvt
One-dimensional marginal CDF function for a Truncated Multivariate Normal and Student t distribution	ptmvnorm.marginal ptmvt.marginal
Quantiles of the Truncated Multivariate Normal Distribution in one dimension	qtmvnorm.marginal
Sampling Random Numbers From The Truncated Multivariate Normal Distribution	rtmvnorm rtmvnorm.sparseMatrix
Sampling Random Numbers From The Truncated Multivariate Normal Distribution With Linear Constraints	rtmvnorm2
Sampling Random Numbers From The Truncated Multivariate Student t Distribution	rtmvt
Truncated Multivariate Normal Density	dtmvnorm