Dissertation/Thesis Abstract

Objective Bayesian inference for stress-strength models and Bayesian ANOVA
by Min, Xiaoyi, Ph.D., University of Missouri - Columbia, 2012, 128; 3537873
Abstract (Summary)

First of all, for estimating the reliabilities in Weibull stress-strength models, some matching priors are derived based on a modified profile likelihood. Simulation studies show that these matching priors perform well with small sample sizes. Next, a generalized Zellner's g-prior is proposed for model selection in linear models with grouped covariates. The marginal likelihood function and a simple closed form of it are derived. The issue of computing the Bayes factors is addressed, and the performance of the Bayes factors is examined by numerical studies. Finally, the Bayes factors under the proposed prior in some 2-way ANOVA models are proved to be consistent.

Keywords: ANOVA models, Bayes factor, consistency, marginal likelihood, matching priors, modified profile likelihood, stress-strength model, Weibull distribution, Zellner's g-prior.

Indexing (document details)
Advisor: Sun, Dongchu
Commitee: Chakraborty, Sounak, He, Zhuoqiong, Rouder, Jeffrey, Speckman, Paul
School: University of Missouri - Columbia
Department: Statistics
School Location: United States -- Missouri
Source: DAI-B 74/07(E), Dissertation Abstracts International
Subjects: Statistics
Keywords: Bayesian inference, Marginal likelihood, Matching priors, Stress-strength models
Publication Number: 3537873
ISBN: 978-1-267-99397-7
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