Nonlinear regression with R.

Autor/inn/en	Ritz, Christian; Streibig, Jens Carl
Titel	Nonlinear regression with R.
Quelle	New York, NY: Springer (2008), XI, 144 S. PDF als Volltext Link als defekt meldenVerfügbarkeit
Reihe	Use R!
Beigaben	grafische Darstellungen; Literaturangaben S. [139]-142
Zusatzinformation	Inhaltsangabe
Sprache	englisch
Dokumenttyp	online; gedruckt; Monographie
ISBN	0-387-09615-9; 978-0-387-09615-5
DOI	10.1007/978-0-387-09616-2
Schlagwörter	Hypothese; Diagnose; Prüfung; Datenanalyse; Programmiersprache; Statistik; Daten; Modell; Wert
Abstract	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. The book begins with an introduction on how to fit nonlinear regression models in R. Subsequent chapters explain in more depth the salient features of the fitting function nls (), the use of model diagnostics, the remedies for various model departures, and how to do hypothesis testing. In the final chapter grouped-data structures, including an example of a nonlinear mixed-effects regression model, are considered. (DIPF/Orig.).
Erfasst von	DIPF \| Leibniz-Institut für Bildungsforschung und Bildungsinformation, Frankfurt am Main
Update	2011/4