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A New Recursive Estimation Method for Single Input Single Output Models

par Ouakasse, Abdelhamid ;Melard, Guy
Référence Journal of time series analysis, 38, 3, page (417-457)
Publication Publié, 2017-05

Article révisé par les pairs

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Résumé :

This article is devoted to a new recursive estimation method for dynamic time series models, more precisely for single input single output models. In that method, the recurrence for updating the Hessian is avoided, but the recurrence for updating the estimator makes use of the Fisher information matrix. The asymptotic properties, consistency and asymptotic normality, of the new estimator are obtained under weak assumptions. Monte Carlo experiments and examples indicate that the estimates converge well, comparatively with alternative methods.