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Statistical tools for nonlinear regression. A practical guide with S-PLUS examples. (English) Zbl 0867.62059
Springer Series in Statistics. New York, NY: Springer. ix, 154 p. (1996).
The book is devoted to nonlinear regression analysis with independent errors. The theoretical grounds are not developed, the authors explain the solutions using intuitive arguments.
The first chapter introduces several examples. Each example illustrates a different problem. The authors show how to methodically handle practical problems by using parametric nonlinear regression models. Chapter 2 is devoted to the accuracy of estimators, confidence intervals and tests. Chapter 3 introduces some new examples and presents methods for handling nonlinear regression models when the variances are heterogeneous with a few or no replications. Chapter 4 is devoted to diagnostics of model misspecification. Chapter 5 describes how to calculate prediction and calibration confidence intervals. At the end of each chapter the authors provide a step-by-step description of the $$S$$-PLUS statistical system.
Reviewer: N.Leonenko (Kiev)

MSC:
 62J02 General nonlinear regression 62-01 Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics 62-04 Software, source code, etc. for problems pertaining to statistics 62J20 Diagnostics, and linear inference and regression