The multivariate normal and the multivariate t distributions belong to the most widely used multivariate distributions in statistics, quantitative risk management, and insurance. In contrast to the multivariate normal distribution, the parameterization of the multivariate t distribution does not correspond to its moments. This, paired with a non-standard implementation in the R package mvtnorm, provides traps for working with the multivariate t distribution. In this paper, common traps are clarified and corresponding recent changes to mvtnorm are presented.
mvtnorm, MASS, evir, mnormt, QRM
Distributions, Multivariate, Environmetrics, ExtremeValue, Econometrics, Finance, NumericalMathematics, Pharmacokinetics, Psychometrics, Robust, SocialSciences
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For attribution, please cite this work as
Hofert, "The R Journal: On Sampling from the Multivariate t Distribution", The R Journal, 2013
BibTeX citation
@article{RJ-2013-033,
author = {Hofert, Marius},
title = {The R Journal: On Sampling from the Multivariate t Distribution},
journal = {The R Journal},
year = {2013},
note = {https://doi.org/10.32614/RJ-2013-033},
doi = {10.32614/RJ-2013-033},
volume = {5},
issue = {2},
issn = {2073-4859},
pages = {129-136}
}