Griffin, Jim E. (2006) On the Bayesian analysis of species sampling mixture models for density estimation. Working Paper. University of Warwick. Centre for Research in Statistical Methodology, Coventry.

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Abstract

The mixture of normals model has been extensively applied to density estimation problems. This paper proposes an alternative parameterisation that naturally leads to new forms of prior distribution. The parameters can be interpreted as the location, scale and smoothness of the density. Priors on these parameters are often easier to specify. Alternatively, improper and default choices lead to automatic Bayesian density estimation. The ideas are extended to multivariate density estimation.

Item Type:	Working or Discussion Paper (Working Paper)
Subjects:	Q Science > QA Mathematics
Divisions:	Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH):	Mixture distributions (Probability theory)
Series Name:	Working papers
Publisher:	University of Warwick. Centre for Research in Statistical Methodology
Place of Publication:	Coventry
Date:	2006
Volume:	Vol.2006
Number:	No.13
Number of Pages:	21
Status:	Not Peer Reviewed
Access rights to Published version:	Open Access
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URI:	http://wrap.warwick.ac.uk/id/eprint/35572

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