A Novel Bayes Factor for Inverse Model Selection Problem based on Inverse Reference Distribution
Journal Title: International Journal of Mathematics and Statistics Invention - Year 2017, Vol 5, Issue 6
Abstract
Statistical model selection problem can be divided into two broad categories based on Forward and Inverse problem. Compared to a wealthy of literature available for Forward model selection, there are very few methods applicable for Inverse model selection context. In this article we propose a novel Bayes factor for model selection in Bayesian Inverse Problem context. The proposed Bayes Factor is specially designed for Inverse problem with the help of Inverse Reference Distribution (IRD). We will discuss our proposal from decision theoretic perspective.
Authors and Affiliations
Debashis Chatterjee
Keywords
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