Non singularity of the asymptotic Fisher information matrix in hidden Markov models

Randal Douc (1)

1 CMAP - Centre de Mathématiques Appliquées - Ecole Polytechnique

In this paper, we consider a parametric hidden Markov model where the hidden state space is non necessarily finite. We provide a necessary and sufficient condition for the invertibility of the limiting Fisher information matrix.

Mots clés: Asymptotic normality; Fisher information matrix; hidden Markov model; identifiability; maximum likelihood

Domaines: Statistiques [math.ST]

Randal Douc. Non singularity of the asymptotic Fisher information matrix in hidden Markov models. 2005. ⟨hal-00014504⟩