Mathematics and Its Applications

By: Andrej PÃ¡zman

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Hardcover | 30 June 1993

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Hardcover
276 Pages

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24.77 x 18.42 x 2.54

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Nonlinear statistical modelling is an area of growing importance. This monograph presents mostly new results and methods concerning the nonlinear regression model.
Among the aspects which are considered are linear properties of nonlinear models, multivariate nonlinear regression, intrinsic and parameter effect curvature, algorithms for calculating the L₂-estimator and both local and global approximation. In addition to this a chapter has been added on the large topic of nonlinear exponential families.
The volume will be of interest to both experts in the field of nonlinear statistical modelling and to those working in the identification of models and optimization, as well as to statisticians in general.

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Introduction	p. 1
Linear regression models	p. 7
Linear methods in nonlinear regression models	p. 34
Univariate regression models	p. 55
The structure of a multivariate nonlinear regression model and properties of L[subscript 2] estimators	p. 80
Nonlinear regression models: computation of estimators and curvatures	p. 113
Local approximations of probability densities and moments of estimators	p. 131
Global approximations of densities of L[subscript 2] estimators	p. 154
Statistical consequences of global approximations especially in flat models	p. 192
Nonlinear exponential families	p. 215
References	p. 248
Basic symbols	p. 255
Subject index	p. 258
Table of Contents provided by Blackwell. All Rights Reserved.

Mathematics and Its Applications

At a Glance

Hardcover

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How to return your order

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