mvnfast: Fast Multivariate Normal and Student's t Methods

Provides computationally efficient tools related to the multivariate normal and Student's t distributions. The main functionalities are: simulating multivariate random vectors, evaluating multivariate normal or Student's t densities and Mahalanobis distances. These tools are very efficient thanks to the use of C++ code and of the OpenMP API.

Version: 0.1.7
Imports: Rcpp (≥ 0.10.4)
LinkingTo: Rcpp, RcppArmadillo, BH
Suggests: knitr, testthat, mvtnorm, microbenchmark, MASS, plyr, RhpcBLASctl
Published: 2016-10-10
Author: Matteo Fasiolo, using the C++ parallel RNG of Thijs van den Berg and Ziggurat algorithm of Jens Maurer and Steven Watanabe (boost)
Maintainer: Matteo Fasiolo <matteo.fasiolo at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2.0)]
Copyright: see file COPYRIGHTS
NeedsCompilation: yes
Citation: mvnfast citation info
CRAN checks: mvnfast results


Reference manual: mvnfast.pdf
Vignettes: mvnfast_vignette
Package source: mvnfast_0.1.7.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Mavericks binaries: r-release: mvnfast_0.1.7.tgz, r-oldrel: mvnfast_0.1.7.tgz
Old sources: mvnfast archive

Reverse dependencies:

Reverse depends: BayesSummaryStatLM
Reverse imports: heemod, mmtfa, simstudy, VARsignR


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