An index sampling algorithm for the Bayesian analysis of a class of model selection problems

In this paper, we present an application of the Gibbs sampler yielding an algorithm which facilitates the Bayesian analysis of a class of data partitioning or model selection problems. The resulting index sampling algorithm is applied to a univariate mean-shift outlier model for the purpose of illustration.

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