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...

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Bibliographic Details

Main Author:	Tanizaki, Hisashi (Author)
Format:	Electronic eBook
Language:	English
Published:	Berlin, Heidelberg Springer Berlin Heidelberg 1996
Edition:	2nd ed. 1996
Subjects:	Economic Theory/Quantitative Economics/Mathematical Methods Statistics for Business, Management, Economics, Finance, Insurance Economic theory Statistics  Schätztheorie Filtertheorie Nichtlineare Filterung Filter > Stochastik Nichtlineares Filter
Online Access:	BTU01 Volltext
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 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
Physical Description:	1 Online-Ressource (XIX, 256 p. 1 illus)
ISBN:	9783662032237
DOI:	10.1007/978-3-662-03223-7