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Kalman recursion generalizations and their applications

Abstract : We consider state space models where the observations are multicategorical and longitudinal, and the state is described by CHARN models. We estimate the state by generalized Kalman recursions, which rely on a variety of particle filters and EM algorithm. Our results are applied to estimating the latent trait in quality of life, and this furnishes an alternative and a generalization of existing methods. These results are illustrated by numerical simulations and an application to real data in the quality of life of patients surged for breast cancer
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Submitted on : Tuesday, May 15, 2018 - 9:29:07 AM
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Sadeq Kadhim. Kalman recursion generalizations and their applications. Statistics [math.ST]. Université de Lorraine, 2018. English. ⟨NNT : 2018LORR0030⟩. ⟨tel-01791912⟩

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