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Nonlinear Filters: Estimation and Applications [Hardcover]

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Item description for Nonlinear Filters: Estimation and Applications by Hisashi Tanizaki...

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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Item Specifications...

Pages   254
Est. Packaging Dimensions:   Length: 9.4" Width: 6.2" Height: 0.8"
Weight:   1.1 lbs.
Binding  Hardcover
Release Date   Aug 16, 1996
Publisher   Springer
ISBN  3540613269  
ISBN13  9783540613268  

Availability  103 units.
Availability accurate as of Oct 26, 2016 11:42.
Usually ships within one to two business days from La Vergne, TN.
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More About Hisashi Tanizaki

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Product Categories

1Books > Special Features > New & Used Textbooks > Business & Finance > Economics > History & Theory
2Books > Special Features > New & Used Textbooks > Sciences > Mathematics > Statistics
3Books > Subjects > Business & Investing > Economics > General
4Books > Subjects > Business & Investing > Economics > Statistics
5Books > Subjects > Business & Investing > Economics > Theory
6Books > Subjects > Professional & Technical > Professional Science > Mathematics > Applied > Statistics
7Books > Subjects > Science > General
8Books > Subjects > Science > Mathematics > Applied > Probability & Statistics

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