Nonlinear Filters

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Nonlinear Filters

Tanizaki

Rok vydania: 1996

Vydavateľ: Springer

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O knihe:

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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Podrobnosti o titule (výrobné údaje):

Vydavateľstvo: Springer

Rok vydania: 1996

Vydanie: 2nd rev. a

ISBN: 978-3-540-61326-8

(9783540613268)

Väzba: tvrdá