TY  - JOUR
AB  - This paper presents two types of symmetric scale mixture probability distributions which include the normal, Student t, Pearson Type VII, variance gamma, exponential power, uniform power and generalised t (GT) distributions. Expressing a symmetric distirbution into a scale mixture for enables efficient Bayersian Markov chain Monte Carlo (MCMC) algorithms in the implementation of complicated statistical models. Moreover, the mixing parameters, a by-product of the scale mixtures representation, can be used to identify possible outliers. this paper also proposes a uniform scale mixture representation for the GT density and demonstrates how this density representation alleviates the computational burden of the Gibbs sampler.
AU  - Choy, S
AU  - Chan, JS
DA  - 2008/01/01
DO  - 10.1111/j.1467-842X.2008.00504.x
EP  - 146
JO  - Australian & New Zealand Journal of Statistics
PB  - Blackwell Publishing Ltd
PY  - 2008/01/01
SP  - 135
TI  - Scale mixtures distributions in statistical modelling
VL  - 50
Y1  - 2008/01/01
Y2  - 2026/07/27
ER  -