Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/22041
Authors: 
DeJong, David Neil
Dharmarajan, Hariharan
Liesenfeld, Roman
Richard, Jean-François
Year of Publication: 
2007
Series/Report no.: 
Economics working paper / Christian-Albrechts-Universität Kiel, Department of Economics 2007,25
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.
Subjects: 
particle filter
adaption
efficient importance sampling
kernel density approximation
Document Type: 
Working Paper

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