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.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!