Statistical Tools for Nonlinear Regression

A Practical Guide with S-PLUS and R Examples

Sylvie Huet, M.-A. Poursat, Emmanuel Jolivet, Annie Bouvier - Collection Springer Series In Statistics

234 pages, parution le 24/11/2003

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Résumé

Statistical Tools for Nonlinear Regression, Second Edition, presents methods for analyzing data using parametric nonlinear regression models. The new edition has been expanded to include binomial, multinomial and Poisson non-linear models. Using examples from experiments in agronomy and biochemistry, it shows how to apply these methods. It concentrates on presenting the methods in an intuitive way rather than developing the theoretical backgrounds.

The examples are analyzed with the free software nls2 updated to deal with the new models included in the second edition. The nls2 package is implemented in S-PLUS and R. Its main advantages are to make the model building, estimation and validation tasks, easy to do. More precisely, Complex models can be easily described using a symbolic syntax. The regression function as well as the variance function can be defined explicitly as functions of independent variables and of unknown parameters or they can be defined as the solution to a system of differential equations.
Moreover, constraints on the parameters can easily be added to the model. It is thus possible to test nested hypotheses and to compare several data sets.
Several additional tools are included in the package for calculating confidence regions for functions of parameters or calibration intervals, using classical methodology or bootstrap. Some graphical tools are proposed for visualizing the fitted curves, the residuals, the confidence regions, and the numerical estimation procedure.

L'auteur - Emmanuel Jolivet

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Sommaire

Nonlinear regression model and parameter estimation
Accuracy of estimators, confidence intervals and tests
Variance estimation
Diagnostics of model misspecification
Calibration and prediction
Binomial non-linear models
Multinomial and Poisson non-linear models

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	Sylvie Huet, M.-A. Poursat, Emmanuel Jolivet, Annie Bouvier
Collection	Springer Series In Statistics
Parution	24/11/2003
Nb. de pages	234
Format	16 x 24
Couverture	Broché
Poids	500g
Intérieur	Noir et Blanc
EAN13	9780387400815
ISBN13	978-0-387-40081-5