Posterior consistency for partially observed Markov models

Jeudi 23 novembre 2017 14:00-15:00 - Randal Douc - Télécom SudParis

Résumé : We establish the posterior consistency for a parametrized family of partially observed, fully dominated Markov models. The prior is assumed to assign positive probability to all neighborhoods of the true parameter, for a distance induced by the expected Kullback-Leibler divergence between the family members’ Markov transition densities. This assumption is easily checked in general. In addition, we show that the posterior consistency is implied by the consistency of the maximum likelihood estimator. The result is extended to possibly non-compact parameter spaces and non-stationary observations. Finally, we check our assumptions on a linear Gaussian model and a well-known stochastic volatility model.
Joint work with Francois Roueff and Jimmy Olsson.

Lieu : Salle 117/119 du bâtiment 425

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