9780387400815 - statistical tools for nonlinear regression: a practical guide with s-plus and r examples (springer series in statistics) von huet, sylvie; bouvier, anne; poursat, marie-anne; jolivet, emmanuel (3 Ergebnisse)
Sprache: Englisch
Verlag: Springer 2004
Serie: Springer Series in Statistics, Buch 67 von 160. Buch 67 von 160 - Springer Series in Statistics
- Hardcover
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Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,600grams, ISBN:9780387400815.
Statistical Tools for Nonlinear Regression: A Practical Guide With S-PLUS and R Examples (Springer Series in Statistics)
Huet, Sylvie; Bouvier, Anne; Poursat, Marie-Anne; Jolivet, Emmanuel
Sprache: Englisch
Verlag: Springer 2003
Serie: Springer Series in Statistics, Buch 67 von 160. Buch 67 von 160 - Springer Series in Statistics
- Hardcover
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections
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Zustand: New. In.
Sprache: Englisch
Verlag: Springer, Copernicus 2003
Serie: Springer Series in Statistics, Buch 67 von 160. Buch 67 von 160 - Springer Series in Statistics
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 fr…om 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.
