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Weiss-Weinstein bound for change-point estimation

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Abstract

We compute the Weiss-Weinstein bound in the context of change-point estimation in a multivariate time series whatever the considered distribution of the data as well the prior. Closed-form expressions are then given in the case of Gaussian observations with change of mean and variance and in the case of parameter change in a Poisson distribution. The proposed bound is shown to be tighter than the previous bounds which were originally derived in the deterministic context and provides a better approximation of the maximum a posteriori estimator global mean square error.
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Dates and versions

hal-01234929 , version 1 (27-11-2015)

Licence

Attribution - CC BY 4.0

Identifiers

  • HAL Id : hal-01234929 , version 1

Cite

Lucien Bacharach, Alexandre Renaux, Mohammed Nabil El Korso, Eric Chaumette. Weiss-Weinstein bound for change-point estimation. IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2015) , Dec 2015, Cancun, Mexico. ⟨hal-01234929⟩
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