Parameter Cascading Method for Functional Data Analysis
Language: English
Published by LAP LAMBERT Academic Publishing Apr 2017, 2017
- Softcover
- New
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
AbeBooks seller since January 11, 2012
Condition: New
£ 61.92
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This item is printed on demand - it takes 3-4 days longer - Neuware -Many statistical models involve three distinct groups of variables: local or nuisance parameters, global or structural parameters, and complexity parameters. In this book, we introduce the parameter cascading method to estimate these statistical models, which treats one group of parameters as an explicit or implicit function of other parameters. The dimensionality of the parameter space is reduced, and the optimization surface becomes smoother. The Newton-Raphson algorithm is applied to estimate these three distinct groups of parameters in three levels of optimization, with the gradients and Hessian matrices written out analytically by the Implicit Function Theorem if necessary and allowing for different criteria for each level of optimization. Moreover, variances of global parameters are estimated by the Delta method and include the variation coming from complexity parameters. We also propose three applications of the parameter cascading method in functional data analysis, include adaptive penalized smoothing, estimating the generalized semiparametric additive models and inferring parameters in differential equations. 240 pp. Englisch.…
Seller Inventory # 9783330072381
- Title
- Parameter Cascading Method for Functional Data Analysis
- Author
- Jiguo Cao
- Publisher
- LAP LAMBERT Academic Publishing Apr 2017
- Publication year
- 2017
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 3330072385
- ISBN 13
- 9783330072381
- Item weight
- 375 grams
- Dimensions
- 220x150x15 mm
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About the Author
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BuchWeltWeit Ludwig Meier e.K.
Bergisch Gladbach, Germany
AbeBooks seller since January 11, 2012
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