Package: mvtnorm 1.3-4

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Torsten Hothorn

mvtnorm: Multivariate Normal and t Distributions

Computes multivariate normal and t probabilities, quantiles, random deviates, and densities. Log-likelihoods for multivariate Gaussian models and Gaussian copulae parameterised by Cholesky factors of covariance or precision matrices are implemented for interval-censored and exact data, or a mix thereof. Score functions for these log-likelihoods are available. A class representing multiple lower triangular matrices and corresponding methods are part of this package.

Authors:Alan Genz [aut], Frank Bretz [aut], Tetsuhisa Miwa [aut], Xuefei Mi [aut], Friedrich Leisch [ctb], Fabian Scheipl [ctb], Bjoern Bornkamp [ctb], Martin Maechler [ctb], Torsten Hothorn [aut, cre]

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mvtnorm.pdf |mvtnorm.html✨
mvtnorm/json (API)
NEWS

# Install 'mvtnorm' in R:
install.packages('mvtnorm', repos = c('https://r-forge.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://r-forge.r-project.org/projects/mvtnorm

Uses libs:
  • openblas– Optimized BLAS

On CRAN:

Conda:

fortranopenblas

15.44 score 2.8k packages 14k scripts 349k downloads 67 mentions 58 exports 0 dependencies

Last updated from:fc07e2650b. Checks:13 OK. Indexed: yes.

TargetResultTotal timeArtifact
linux-devel-arm64OK199
linux-devel-x86_64OK197
source / vignettesOK209
linux-release-arm64OK192
linux-release-x86_64OK187
macos-devel-arm64OK163
macos-devel-x86_64OK248
macos-release-arm64OK200
macos-release-x86_64OK316
windows-develOK222
windows-releaseOK202
windows-oldrelOK203
wasm-releaseOK81

Exports:as.cholas.invcholas.ltMatricesas.syMatriceschol2corchol2covchol2invcholchol2pcchol2precond_mvnormcondDistCrossprodDcholdepermadestandardizediagonalsdiagonals<-dmvnormdmvtGenzBretzinvchol2cholinvchol2corinvchol2covinvchol2pcinvchol2preinvcholDis.cholis.invcholis.ltMatricesis.syMatricesldmvnormldpmvnormlLgradlogdetLower_trilpmvnormlpRRltMatricesmarg_mvnormmargDistMiwaMultmvnormpmvnormpmvtqmvnormqmvtrmvnormrmvtsldmvnormsldpmvnormslpmvnormslpRRstandardizesyMatricesTcrossprodTVPACKvectrick

Dependencies:

Multivariate Normal Log-likelihoods in the mvtnorm Package

Rendered fromlmvnorm_src.Rnwusingutils::Sweaveon Feb 06 2026.

Last update: 2025-12-12
Started: 2023-03-28

Using mvtnorm

Rendered fromMVT_Rnews.Rnwusingutils::Sweaveon Feb 06 2026.

Last update: 2024-05-08
Started: 2013-09-04

Readme and manuals

Help Manual

Help pageTopics
Multivariate Normal and t Distributionsmvtnorm-package mvtnorm
Choice of Algorithm and Hyper ParametersGenzBretz Miwa TVPACK
(Experimental) User Interface to Multiple Multivariate Normal Distributionsaperm.mvnorm condDist condDist.mvnorm lLgrad lLgrad.mvnorm logLik.mvnorm margDist margDist.mvnorm mvnorm simulate.mvnorm
Multivariate Normal Log-likelihood and Score Functionsldmvnorm ldpmvnorm lpmvnorm sldmvnorm sldpmvnorm slpmvnorm
Multivariate Normal Log-likelihood and Score Functions for Reduced Rank CovarianceslpRR slpRR
Multiple Lower Triangular or Symmetric Matricesadddiag aperm.chol aperm.invchol aperm.ltMatrices aperm.syMatrices as.array.ltMatrices as.array.syMatrices as.chol as.invchol as.ltMatrices as.ltMatrices.ltMatrices as.ltMatrices.syMatrices as.syMatrices chol.syMatrices chol2cor chol2cov chol2invchol chol2pc chol2pre Crossprod crossprod.ltMatrices crossprod.syMatrices Dchol deperma destandardize diagonals diagonals.integer diagonals.ltMatrices diagonals.matrix diagonals.syMatrices diagonals<- diagonals<-.ltMatrices diagonals<-.syMatrices invchol2chol invchol2cor invchol2cov invchol2pc invchol2pre invcholD is.chol is.invchol is.ltMatrices is.syMatrices logdet Lower_tri ltMatrices Mult Mult.ltMatrices Mult.syMatrices solve.ltMatrices standardize syMatrices Tcrossprod tcrossprod.ltMatrices tcrossprod.syMatrices vectrick
Marginal and Conditional Multivariate Normal Distributionscond_mvnorm marg_mvnorm
Multivariate Normal Density and Random Deviatesdmvnorm rmvnorm
The Multivariate t Distributiondmvt rmvt
Multivariate Normal Distributionpmvnorm
Multivariate t Distributionpmvt
Quantiles of the Multivariate Normal Distributionqmvnorm
Quantiles of the Multivariate t Distributionqmvt
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