Nonsubjective Bayes testing-an overview

Ghosh, Jayanta K. ; Samanta, Tapas (2002) Nonsubjective Bayes testing-an overview Journal of Statistical Planning and Inference, 103 (1-2). pp. 205-223. ISSN 0378-3758

Full text not available from this repository.

Official URL:

Related URL:


In Bayesian model selection, or hypothesis testing, difficulties arise when improper noninformative priors are used to calculate the Bayes factors. Several methods have been proposed to remove these difficulties. In this paper we discuss a unified derivation of some of these methods which shows that in some qualitative or conceptual sense, these methods are no more than a fixed number of observations away from a Bayes factor based on noninformative priors, and are close to each other and to certain Bayes factors based on low information proper priors which include priors recommended by Jeffreys (1961).

Item Type:Article
Source:Copyright of this article belongs to Elsevier Science.
Keywords:Bayes Factor; Model Selection; Noninformative Prior; Training Sample
ID Code:22531
Deposited On:24 Nov 2010 08:23
Last Modified:02 Jun 2011 06:52

Repository Staff Only: item control page