mvpd: Multivariate Product Distributions

In mvpd: Multivariate Product Distributions for Elliptically Contoured Distributions

Multivariate Product Distributions

Description

The purpose of this package is to offer density, probability, and random variate generating (abbreviated as [d/p/r], respectively) functions for multivariate distributions that can be represented as a product distribution. Specifically, the package will primarily focus on the product of a multivariate normal distribution and a univariate random variable. These product distributions are called Scale Mixtures of Multivariate Normal Distributions, and for particular choices of the univariate random variable distribution the resultant product distribution may be a family of interest. For instance, the square-root of a positive stable random variable multiplied by a multivariate normal distribution is the multivariate subgaussian stable distribution. Product distribution theory is applied for implementing their computation.

Multivariate subgaussian stable distributions

dmvss – multivariate subgaussian stable distribution density

pmvss – multivariate subgaussian stable distribution probabilities

rmvss – multivariate subgaussian stable distribution random variates

pmvss_mc – Monte Carlo version of probabilities, using rmvss

fit_mvss – Fit a multivariate subgaussian stable distribution (e.g. estimate parameters given data)

Author(s)

Maintainer: Bruce Swihart [e-mail] (ORCID)

See Also

Useful links:

• https://github.com/swihart/mvpd

• Report bugs at https://github.com/swihart/mvpd/issues

mvpd documentation built on Sept. 3, 2023, 5:07 p.m.