Bayesian optimization analysis with ML-II ε-contaminated prior

In this paper we derive the predictive density function of a future observation when prior distribution for unknown mean of a normal population is a Type-II maximum likelihood ε-contaminated prior. The derived predictive distribution is applied to the problem of optimization of a regression nature in the decisive prediction framework.

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Year of publication:	2008
Authors:	Sinha, Pankaj ; Bansal, Ashok
Published in:	Journal of Applied Statistics. - Taylor & Francis Journals, ISSN 0266-4763. - Vol. 35.2008, 2, p. 203-211
Publisher:	Taylor & Francis Journals
Subject:	ε-contaminated prior \| type II maximum likelihood technique \| optimization analysis \| decisive prediction

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Extent:	text/html
Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005278882