We introduce a new method for drawing state variables in Gaussian state space models from their conditional distribution given parameters and observations. Unlike standard methods, our method does not involve Kalman filtering. We show that for some important cases, our method is computationally more efficient than standard methods in the literature. We consider two applications of our method.
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Paper provided by Universite de Montreal, Departement de sciences economiques in its series Cahiers de recherche with number
2007-06.
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