Nonlinear Statistical Models
Author:   Andrej Pázman
Publisher:   Springer
Edition:   1993 ed.
Volume:   254
ISBN:  

9780792322474


Pages:   260
Publication Date:   30 June 1993
Format:   Hardback
Availability:   In Print   Availability explained
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Nonlinear Statistical Models


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Overview

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.

Full Product Details

Author:   Andrej Pázman
Publisher:   Springer
Imprint:   Springer
Edition:   1993 ed.
Volume:   254
Dimensions:   Width: 15.60cm , Height: 1.70cm , Length: 23.40cm
Weight:   1.250kg
ISBN:  

9780792322474


ISBN 10:   0792322479
Pages:   260
Publication Date:   30 June 1993
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

1 Linear regression models.- 2 Linear methods in nonlinear regression models.- 3 Univariate regression models.- 4 The structure of a multivariate nonlinear regression model and properties of L2 estimators.- 5 Nonlinear regression models: computation of estimators and curvatures.- 6 Local approximations of probability densities and moments of estimators.- 7 Global approximations of densities of L2 estimators.- 8 Statistical consequences of global approximations especially in flat models.- 9 Nonlinear exponential families.- References.- Basic symbols.

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