Convergence assessment techniques for Markov chain Monte Carlo
Statistics and Computing
Quantitative convergence assessment for Markov chain Monte Carlo via cusums
Statistics and Computing
Comparison of methodologies to assess the convergence of Markov chain Monte Carlo methods
Computational Statistics & Data Analysis
Bayesian inference in non-Gaussian factor analysis
Statistics and Computing
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In this paper, we propose to monitor a Markov chain sampler using the cusum path plot of a chosen one-dimensional summary statistic. We argue that the cusum path plot can bring out, more effectively than the sequential plot, those aspects of a Markov sampler which tell the user how quickly or slowly the sampler is moving around in its sample space, in the direction of the summary statistic. The proposal is then illustrated in four examples which represent situations where the cusum path plot works well and not well. Moreover, a rigorous analysis is given for one of the examples. We conclude that the cusum path plot is an effective tool for convergence diagnostics of a Markov sampler and for comparing different Markov samplers.