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An Efficient Filtering Approach to Likelihood Approximation for State-Space Representations

David DeJong (), Hariharan Dharmarajan, Roman Liesenfeld and Jean-Francois Richard

No 2007-25, Economics Working Papers from Christian-Albrechts-University of Kiel, Department of Economics

Abstract: We develop a numerical filtering procedure that facilitates efficient likelihood evaluation in applications involving non-linear and non-gaussian state-space models. The procedure approximates necessary integrals using continuous or piecewise-continuous approximations of target densities. Construction is achieved via efficient importance sampling, and approximating densities are adapted to fully incorporate current information.

Keywords: particle filter; adaption; efficient importance sampling; kernel density approximation (search for similar items in EconPapers)
Date: 2007
New Economics Papers: this item is included in nep-ecm and nep-ets
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