Analysis, detection and correction of misspecified discrete time state space models

Abstract : Misspecifications (i.e. errors on the parameters) of state space models lead to incorrect inference of the hidden states. This paper studies weakly nonlin-ear state space models with additive Gaussian noises and proposes a method for detecting and correcting misspecifications. The latter induce a biased estimator of the hidden state but also happen to induce correlation on innovations and other residues. This property is used to find a well-defined objective function for which an optimisation routine is applied to recover the true parameters of the model. It is argued that this method can consistently estimate the bias on the parameter. We demonstrate the algorithm on various models of increasing complexity.
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Pré-publication, Document de travail
2017
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https://hal.archives-ouvertes.fr/hal-01500238
Contributeur : Salima El Kolei <>
Soumis le : dimanche 2 avril 2017 - 21:01:40
Dernière modification le : vendredi 12 janvier 2018 - 01:51:39
Document(s) archivé(s) le : lundi 3 juillet 2017 - 16:51:26

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  • HAL Id : hal-01500238, version 1
  • ARXIV : 1704.00587

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Salima El Kolei, Frédéric Patras. Analysis, detection and correction of misspecified discrete time state space models. 2017. 〈hal-01500238〉

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