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.

Documentation

Manual: mvnfast.pdf
Vignette: mvnfast_vignette

Maintainer: Matteo Fasiolo <matteo.fasiolo at gmail.com>

Author(s): Matteo Fasiolo, using the C++ parallel RNG of Thijs van den Berg and Ziggurat algorithm of Jens Maurer and Steven Watanabe (boost)

Install package and any missing dependencies by running this line in your R console:

install.packages("mvnfast")

Depends
Imports Rcpp(>=0.10.4)
Suggests knitr, testthat, mvtnorm, microbenchmark, MASS, plyr, RhpcBLASctl
Enhances
Linking to Rcpp, RcppArmadillo, BH
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depends
BayesSummaryStatLM
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imports
esaddle, heemod, horserule, IMIFA, mmtfa, simstudy, VARsignR
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suggests
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enhances
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linking to

Package mvnfast
Materials
URL https://github.com/mfasiolo/mvnfast www.sitmo.com
Task Views
Version 0.2.0
Published 2017-02-18
License GPL (>= 2.0)
BugReports
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks mvnfast check results
Package source mvnfast_0.2.0.tar.gz