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Nonlinear Filters

Estimation and Applications

Springer Berlin,
Buch
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Kurzbeschreibung

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.

Details
Schlagworte

Titel: Nonlinear Filters
Autoren/Herausgeber: Hisashi Tanizaki
Ausgabe: 2nd rev. and enlarged ed. 1996

ISBN/EAN: 9783540613268

Seitenzahl: 256
Format: 23,5 x 15,5 cm
Produktform: Hardcover/Gebunden
Gewicht: 1,260 g
Sprache: Englisch

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