alexa Hierarchical Bayesian Analysis of Changepoint Problems
Biomedical Sciences

Biomedical Sciences

International Journal of Biomedical Data Mining

Author(s): Bradley P Carlin, Alan E Gelfand, Adrian F M Smith

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A general approach to hierarchical Bayes changepoint models is presented. In particular, desired marginal posterior densities are obtained utilizing the Gibbs sampler, an iterative Monte Carlo method. This approach avoids sophisticated analytic and numerical high dimensional integration procedures. We include an application to changing regressions, changing Poisson processes and changing Markov chains. Within these contexts we handle several previously inaccessible problems.

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This article was published in Journal of the Royal Statistical Society. and referenced in International Journal of Biomedical Data Mining

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