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Nonlinear Filters : Estimation and Applications

Author: Hisashi Tanizaki
Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 1996.
Edition/Format:   eBook : Document : English : Second revised and enlarged editionView all editions and formats
Database:WorldCat
Summary:
Nonlinear and nonnormal filters are introduced and developed. Traditional nonlinear filters such as the extended Kalman filter and the Gaussian sum filter give biased filtering estimates, and therefore several nonlinear and nonnormal filters have been derived from the underlying probability density functions. The density-based nonlinear filters introduced in this book utilize numerical integration, Monte-Carlo  Read more...
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Genre/Form: Electronic books
Statistics
Additional Physical Format: Print version:
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Hisashi Tanizaki
ISBN: 9783662032237 3662032236
OCLC Number: 851372266
Description: 1 online resource (xix, 255 pages)
Contents: Introduction --
State-Space Model in Linear Case --
Traditional Nonlinear Filters --
Density Based Nonlinear Filters --
Monte-Carlo Experiments --
Application of Ninlinear Filters --
Prediction and Smoothing --
Summary and Concluding Remarks.
Responsibility: by Hisashi Tanizaki.

Abstract:

Nonlinear and nonnormal filters are introduced and developed. Traditional nonlinear filters such as the extended Kalman filter and the Gaussian sum filter give biased filtering estimates, and therefore several nonlinear and nonnormal filters have been derived from the underlying probability density functions. The density-based nonlinear filters introduced in this book utilize numerical integration, Monte-Carlo integration with importance sampling or rejection sampling and the obtained filtering estimates are asymptotically unbiased and efficient. By Monte-Carlo simulation studies, all the nonlinear filters are compared. Finally, as an empirical application, consumption functions based on the rational expectation model are estimated for the nonlinear filters, where US, UK and Japan economies are compared.

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