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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: 0.2.8
Imports: Rcpp
LinkingTo: Rcpp, RcppArmadillo, BH
Suggests: knitr, rmarkdown, testthat, mvtnorm, microbenchmark, MASS, plyr, RhpcBLASctl
Published: 2023-02-23
DOI: 10.32614/CRAN.package.mvnfast
Author: Matteo Fasiolo [aut, cre], Thijs van den Berg [ctb]
Maintainer: Matteo Fasiolo <matteo.fasiolo at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2.0)]
Copyright: see file COPYRIGHTS
URL: https://github.com/mfasiolo/mvnfast/
NeedsCompilation: yes
Citation: mvnfast citation info
Materials: ChangeLog
In views: HighPerformanceComputing
CRAN checks: mvnfast results

Documentation:

Reference manual: mvnfast.pdf
Vignettes: mvnfast_vignette

Downloads:

Package source: mvnfast_0.2.8.tar.gz
Windows binaries: r-devel: mvnfast_0.2.8.zip, r-release: mvnfast_0.2.8.zip, r-oldrel: mvnfast_0.2.8.zip
macOS binaries: r-release (arm64): mvnfast_0.2.8.tgz, r-oldrel (arm64): mvnfast_0.2.8.tgz, r-release (x86_64): mvnfast_0.2.8.tgz, r-oldrel (x86_64): mvnfast_0.2.8.tgz
Old sources: mvnfast archive

Reverse dependencies:

Reverse imports: assignR, BBSSL, BGGM, bigmatch, bltm, bspcov, clarify, DiPs, discSurv, esaddle, ezECM, forestecology, gasmodel, GloScope, gmvarkit, gratia, hdcuremodels, heemod, IADT, IMIFA, leakyIV, longsurr, MGMM, modsem, MoEClust, MultRegCMP, mvgam, PROsetta, remstimate, shapr, simstudy, SMLE, sparseCov, UNCOVER
Reverse suggests: clustTMB, CPGLIB, fabricatr, nnGarrote, PSGD, RMSS, robStepSplitReg, scDesign3, spBPS, SplitGLM, splitSelect, srlars, stepSplitReg

Linking:

Please use the canonical form https://CRAN.R-project.org/package=mvnfast to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.