Nonlinear Filters: Estimation and Applications
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...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Berlin, Heidelberg
Springer Berlin Heidelberg
1996
|
| Ausgabe: | 2nd ed. 1996 |
| Schlagworte: | |
| Online-Zugang: | BTU01 Volltext |
| Zusammenfassung: | 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 |
| Beschreibung: | 1 Online-Ressource (XIX, 256 p. 1 illus) |
| ISBN: | 9783662032237 |
| DOI: | 10.1007/978-3-662-03223-7 |
Internformat
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| 520 | |a 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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Datensatz im Suchindex
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| author | Tanizaki, Hisashi |
| author_facet | Tanizaki, Hisashi |
| author_role | aut |
| author_sort | Tanizaki, Hisashi |
| author_variant | h t ht |
| building | Verbundindex |
| bvnumber | BV046871889 |
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| ctrlnum | (ZDB-2-SBE)978-3-662-03223-7 (OCoLC)903191843 (DE-599)BVBBV046871889 |
| dewey-full | 330.1 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 330 - Economics |
| dewey-raw | 330.1 |
| dewey-search | 330.1 |
| dewey-sort | 3330.1 |
| dewey-tens | 330 - Economics |
| discipline | Informatik Mathematik Wirtschaftswissenschaften |
| discipline_str_mv | Informatik Mathematik Wirtschaftswissenschaften |
| doi_str_mv | 10.1007/978-3-662-03223-7 |
| edition | 2nd ed. 1996 |
| format | Electronic eBook |
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| id | DE-604.BV046871889 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T15:15:36Z |
| indexdate | 2024-07-10T08:56:08Z |
| institution | BVB |
| isbn | 9783662032237 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032282021 |
| oclc_num | 903191843 |
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| physical | 1 Online-Ressource (XIX, 256 p. 1 illus) |
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| publishDate | 1996 |
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| publisher | Springer Berlin Heidelberg |
| record_format | marc |
| spelling | Tanizaki, Hisashi Verfasser aut Nonlinear Filters Estimation and Applications by Hisashi Tanizaki 2nd ed. 1996 Berlin, Heidelberg Springer Berlin Heidelberg 1996 1 Online-Ressource (XIX, 256 p. 1 illus) txt rdacontent c rdamedia cr rdacarrier 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 Economic Theory/Quantitative Economics/Mathematical Methods Statistics for Business, Management, Economics, Finance, Insurance Economic theory Statistics Schätztheorie (DE-588)4121608-8 gnd rswk-swf Filtertheorie (DE-588)4154392-0 gnd rswk-swf Nichtlineare Filterung (DE-588)4171753-3 gnd rswk-swf Filter Stochastik (DE-588)4128590-6 gnd rswk-swf Nichtlineares Filter (DE-588)4451051-2 gnd rswk-swf Nichtlineares Filter (DE-588)4451051-2 s Filter Stochastik (DE-588)4128590-6 s DE-604 Schätztheorie (DE-588)4121608-8 s Nichtlineare Filterung (DE-588)4171753-3 s Filtertheorie (DE-588)4154392-0 s Erscheint auch als Druck-Ausgabe 9783642082535 Erscheint auch als Druck-Ausgabe 9783540613268 Erscheint auch als Druck-Ausgabe 9783662032244 https://doi.org/10.1007/978-3-662-03223-7 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Tanizaki, Hisashi Nonlinear Filters Estimation and Applications Economic Theory/Quantitative Economics/Mathematical Methods Statistics for Business, Management, Economics, Finance, Insurance Economic theory Statistics Schätztheorie (DE-588)4121608-8 gnd Filtertheorie (DE-588)4154392-0 gnd Nichtlineare Filterung (DE-588)4171753-3 gnd Filter Stochastik (DE-588)4128590-6 gnd Nichtlineares Filter (DE-588)4451051-2 gnd |
| subject_GND | (DE-588)4121608-8 (DE-588)4154392-0 (DE-588)4171753-3 (DE-588)4128590-6 (DE-588)4451051-2 |
| title | Nonlinear Filters Estimation and Applications |
| title_auth | Nonlinear Filters Estimation and Applications |
| title_exact_search | Nonlinear Filters Estimation and Applications |
| title_exact_search_txtP | Nonlinear Filters Estimation and Applications |
| title_full | Nonlinear Filters Estimation and Applications by Hisashi Tanizaki |
| title_fullStr | Nonlinear Filters Estimation and Applications by Hisashi Tanizaki |
| title_full_unstemmed | Nonlinear Filters Estimation and Applications by Hisashi Tanizaki |
| title_short | Nonlinear Filters |
| title_sort | nonlinear filters estimation and applications |
| title_sub | Estimation and Applications |
| topic | Economic Theory/Quantitative Economics/Mathematical Methods Statistics for Business, Management, Economics, Finance, Insurance Economic theory Statistics Schätztheorie (DE-588)4121608-8 gnd Filtertheorie (DE-588)4154392-0 gnd Nichtlineare Filterung (DE-588)4171753-3 gnd Filter Stochastik (DE-588)4128590-6 gnd Nichtlineares Filter (DE-588)4451051-2 gnd |
| topic_facet | Economic Theory/Quantitative Economics/Mathematical Methods Statistics for Business, Management, Economics, Finance, Insurance Economic theory Statistics Schätztheorie Filtertheorie Nichtlineare Filterung Filter Stochastik Nichtlineares Filter |
| url | https://doi.org/10.1007/978-3-662-03223-7 |
| work_keys_str_mv | AT tanizakihisashi nonlinearfiltersestimationandapplications |