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

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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Year of publication:	2007
Authors:	DeJong, David Neil ; Dharmarajan, Hariharan ; Liesenfeld, Roman ; Richard, Jean-François
Institutions:	Institut für Volkswirtschaftslehre, Christian-Albrechts-Universität Kiel
Subject:	particle filter \| adaption \| efficient importance sampling \| kernel density approximation

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Extent:	application/pdf
Series:	Economics Working Papers. - ISSN 2193-2476.
Type of publication:	Book / Working Paper
Language:	English
Notes:	Number 2007,25
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005082902