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

Salima El Kolei (1) , Frédéric Patras (2)

1 ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz]
2 JAD - Laboratoire Jean Alexandre Dieudonné

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.

Mots clés: Kalman filter; Extended Kalman filter; State space models; Mis- specified models; Robust estimation

Domaines: Applications [stat.AP]; Calcul [stat.CO]

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