Description: Statistical Tools for Nonlinear Regression presents methods for analyzing data using parametric nonlinear regression models. Using examples from experiments in agronomy and biochemistry, it shows how to apply the methods. Aimed at scientists who are not familiar with statistical theory, it concentrates on presenting the methods in an intuitive way rather than developing the theoretical grounds. The book includes methods based on classical nonlinear regression theory and more modern methods, such as the bootstrap, that have proven effective in practice. The examples are analyzed with the software nls2 implemented in S-PLUS.

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