A distance-based diagnostic for trans-dimensional Markov chains

Authors:
S. A. Sisson;Y. Fan
Affiliations:
School of Mathematics and Statistics, University of New South Wales, Sydney, Australia 2052;School of Mathematics and Statistics, University of New South Wales, Sydney, Australia 2052
Venue:
Statistics and Computing
Year:
2007

Citing 2
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Abstract

Over the last decade the use of trans-dimensional sampling algorithms has become endemic in the statistical literature. In spite of their application however, there are few reliable methods to assess whether the underlying Markov chains have reached their stationary distribution. In this article we present a distance-based method for the comparison of trans-dimensional Markov chain sample output for a broad class of models. This diagnostic will simultaneously assess deviations between and within chains. Illustration of the analysis of Markov chain sample-paths is presented in simulated examples and in two common modelling situations: a finite mixture analysis and a change-point problem.