Bayesian parametric inference in a nonparametric framework

Walker, Stephen G. and Gutierrez-Pena, Eduardo (2007) Bayesian parametric inference in a nonparametric framework. Test, 16 (1). pp. 188-197. ISSN 1133-0686. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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Official URL
http://dx.doi.org/10.1007/s11749-006-0008-8

Abstract

This paper considers the problem of reporting a "posterior distribution" using a parametric family of distributions while working in a nonparametric framework. This "posterior" is obtained as the solution to a decision problem and can be found via a well-known optimization algorithm

Item Type: Article
Uncontrolled keywords: decision theory; expected utility; nonparametric prior; parametric predictive density DENSITY-ESTIMATION; MIXTURES; INFORMATION; ALGORITHMS; MODELS
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Stephen Holland
Date Deposited: 19 Dec 2007 18:56
Last Modified: 25 Apr 2014 13:47
Resource URI: https://kar.kent.ac.uk/id/eprint/1429 (The current URI for this page, for reference purposes)
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