Pázman A. Nonlinear Statistical Models

Amsterdam: Springer, 1993. - 260p.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.Linear regression models
Linear methods in nonlinear regression models
Univariate regression models
The structure of a multivariate nonlinear regression model and properties of L 2 estimators
Nonlinear regression models: computation of estimators and curvatures
Local approximations of probability densities and moments of estimators
Global approximations of densities of L 2 estimators
Statistical consequences of global approximations especially in flat models
Nonlinear exponential families