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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-François

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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File URL: http://econstor.eu/bitstream/10419/22041/1/EWP-2007-25.pdf
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Bibliographic Info

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
Date of revision:
Handle: RePEc:zbw:cauewp:6339

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Related research

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

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

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