Prior based model checking

TL;DR

This paper introduces a novel model checking approach using Dirichlet process and relative belief, which avoids data double use and prior-data conflict, demonstrating excellent performance across various examples.

Contribution

It presents a new prior-based model checking method combining Dirichlet process and relative belief, offering advantages over traditional techniques.

Findings

Avoids double data use and prior-data conflict

Demonstrates excellent performance in multiple examples

Provides a robust alternative for model checking

Abstract

Model checking procedures are considered based on the use of the Dirichlet process and relative belief. This combination is seen to lead to some unique advantages for this problem. In particular, it avoids double use of the data and prior-data conflict. Several examples have been incorporated, in which the proposed approach exhibits excellent performance.