Exact posterior distributions and model selection criteria for multiple change-point detection problems |
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Authors: | G Rigaill S Robin |
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Institution: | 1.AgroParisTech,UMR 518,Paris,France;2.INRA,UMR 518,Paris,France;3.Département de Transfert,Institut Curie,Paris,France;4.Bioinformatics and Statistics,NKI-AVL,Amsterdam,Netherlands |
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Abstract: | In segmentation problems, inference on change-point position and model selection are two difficult issues due to the discrete
nature of change-points. In a Bayesian context, we derive exact, explicit and tractable formulae for the posterior distribution
of variables such as the number of change-points or their positions. We also demonstrate that several classical Bayesian model
selection criteria can be computed exactly. All these results are based on an efficient strategy to explore the whole segmentation
space, which is very large. We illustrate our methodology on both simulated data and a comparative genomic hybridization profile. |
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Keywords: | |
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