Griffin, Jim E. (2006) On the Bayesian analysis of species sampling mixture models for density estimation. Working Paper. Coventry: University of Warwick. Centre for Research in Statistical Methodology. Working papers, Vol.2006 (No.13).

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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
Official Date:	2006
Dates:	Date Event 2006 Published
Date of first compliant deposit:	1 August 2016
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Status:	Not Peer Reviewed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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