Nonlinear Regression with R - Christian Ritz

R is a rapidly evolving lingua franca of graphical display and statistical analysis of experiments from the applied sciences. Currently, R offers a wide range of functionality for nonlinear regression analysis, but the relevant functions, packages and documentation are scattered across the R environment. This book provides a coherent and unified treatment of nonlinear regression with R by means of examples from a diversity of applied sciences such as biology, chemistry, engineering, medicine and toxicology. R. Subsequent chapters explain the salient features of the main fitting function nls (), the use of model diagnostics, how to deal with various model departures, and carry out hypothesis testing. In the final chapter grouped-data structures, including an example of a nonlinear mixed-effects regression model, are considered. TOC:Introduction.- Getting started.- Starting values and self starters.- More on nls ().- Model diagnostics.- Remedies for model variations.- Uncertainty, hypothesis testing and model selection.- Grouped data.- Appendix A: Datasets and models.- Appendix B: Self starter functions.- Appendix C: Packages and functions.- References.- Index.

Tytuł: Nonlinear Regression with R
Autor:

Christian Ritz

Seria: Use R
Data wydania: luty 2009
Wydawca: Springer-Verlag GmbH
ISBN: 0387096159
EAN: 9780387096155
Wymiary: 235 x 154 x 13