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.

Fast methods for multivariate normal distributions. For details type vignette("mvnfast").


Reference manual

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install.packages("mvnfast") by Matteo Fasiolo, 7 months ago,

Browse source code at

Authors: Matteo Fasiolo [aut, cre] , Thijs van den Berg [ctb]

Documentation:   PDF Manual  

Task views: High-Performance and Parallel Computing with R

GPL (>= 2.0) license

Imports Rcpp

Suggests knitr, rmarkdown, testthat, mvtnorm, microbenchmark, MASS, plyr, RhpcBLASctl

Linking to Rcpp, RcppArmadillo, BH

Imported by BBSSL, BGGM, BayesMRA, DiPs, IMIFA, MGMM, MoEClust, PROsetta, SMLE, SurrogateRegression, VARsignR, bartBMA, bigmatch, bltm, chickn, esaddle, forestecology, gmvarkit, gratia, heemod, horserule, match2C, shapr, simstudy.

Suggested by CPGLIB, SplitGLM, fabricatr, nnGarrote, splitSelect.

See at CRAN