On mean and/or variance mixtures of normal distributions
Statistics Theory
2020-05-15 v1 Statistics Theory
Abstract
Parametric distributions are an important part of statistics. There is now a voluminous literature on different fascinating formulations of flexible distributions. We present a selective and brief overview of a small subset of these distributions, focusing on those that are obtained by scaling the mean and/or covariance matrix of the (multivariate) normal distribution with some scaling variable(s). Namely, we consider the families of mean mixture, variance mixture, and mean-variance mixture of normal distributions. Its basic properties, some notable special/limiting cases, and parameter estimation methods are also described.
Keywords
Cite
@article{arxiv.2005.06883,
title = {On mean and/or variance mixtures of normal distributions},
author = {Sharon X. Lee and Geoffrey J. McLachlan},
journal= {arXiv preprint arXiv:2005.06883},
year = {2020}
}
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10 pages, 0 figures