
The book starts out giving a basic introduction to fitting nonlinear regression models in
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.
| david w lawlor lee child marylynn t quartaroli frank ansley terry brooks | timothy r mayes c m ross hoskins hoskins michael f stagliano stephen j dubner |