A Method for Testing Nested Point Null Hypotheses Using Multiple Bayes Factor

Author: Kim H-J.

Source: Annals of the Institute of Statistical Mathematics, Volume 51, Number 3, September 1999 , pp. 585-602(18)

Publisher: Springer

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Abstract:

As a flexible Bayesian test criterion for nested point null hypotheses, asymmetric and multiple Bayes factors are introduced in the form of a modified Savage-Dickey density ratio. This leads to a simple method for obtaining pairwise comparisons of hypotheses in a statistical experiment with a partition on the parameter space. The method is derived from the fact that in general, the asymmetric Bayes factor can be written as the product of the Savage-Dickey ratio and a correction factor where both terms are easily estimated by means of posterior simulation. Analyses of a censored data problem and a serial correlation problem are illustrated for the method. For these cases, the method is straightforward for specifying distributionally and to implement computationally, with output readily adapted for required tests.

Keywords: Asymmetric and multiple Bayes factors; Savage-Dickey density ratio; Gibbs sampler; point null hypothesis; censored data; serial correlation

Language: English

Document Type: Regular paper

Affiliations: 1: Department of Statistics, Dongguk University, Seoul 100-715, Korea

Publication date: 1999-09-01