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

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Author Info
DeJong, David Neil
Dharmarajan, Hariharan
Liesenfeld, Roman
Richard, Jean-Francois
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. --

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Paper provided by Christian-Albrechts-University of Kiel, Department of Economics in its series Economics Working Papers with number 2007,25.

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Date of creation: 2007
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Handle: RePEc:zbw:cauewp:6339

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Web page: http://www.wiso.uni-kiel.de/econ/

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Related research
Keywords: particle filter; adaption; efficient importance sampling; kernel density approximation;

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  1. Jesús Fernández-Villaverde & Juan F Rubio-Ramírez, 2007. "How Structural Are Structural Parameters?," Levine's Bibliography 843644000000000057, UCLA Department of Economics. [Downloadable!]
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