Scale mixtures distributions in statistical modelling

Choy, S; Chan, JS

Scale mixtures distributions in statistical modelling

Choy, S Chan, JS

Permalink

Publisher:: Blackwell Publishing Ltd
Publication Type:: Journal Article
Citation:: Australian & New Zealand Journal of Statistics, 2008, 50 (2), pp. 135 - 146
Issue Date:: 2008-01

Closed Access

	Filename	Description	Size
	2007003833OK.pdf		121.38 kB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Choy, S	en_US
dc.contributor.author	Chan, JS	en_US
dc.date.issued	2008-01	en_US
dc.identifier.citation	Australian & New Zealand Journal of Statistics, 2008, 50 (2), pp. 135 - 146	en_US
dc.identifier.issn	1369-1473	en_US
dc.identifier.uri	http://hdl.handle.net/10453/14465
dc.description.abstract	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.	en_US
dc.publisher	Blackwell Publishing Ltd	en_US
dc.relation.ispartof	Australian & New Zealand Journal of Statistics	en_US
dc.relation.isbasedon	10.1111/j.1467-842X.2008.00504.x	en_US
dc.subject.classification	Statistics & Probability	en_US
dc.title	Scale mixtures distributions in statistical modelling	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	50	en_US
utslib.for	0104 Statistics	en_US
utslib.for	1403 Econometrics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
utslib.copyright.status	closed_access
pubs.declined	1970-01-01T00:00:00.0+1000
pubs.consider-herdc	true	en_US
pubs.deleted	1970-01-01T00:00:00.0+1000
pubs.issue	2	en_US
pubs.volume	50	en_US

Abstract:

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.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/14465