Robust nonlinear regression: with applications using R (1st)

Robust Nonlinear Regression: with Applications using R develops new methods in robust nonlinear regression and implements a set of objects and functions in S-language, under SPLUS and R software. The software covers a wide range of robust nonlinear fitting and inferences, and is designed to provide facilities for computer users to define their own nonlinear models as an object, and fit models using classic and robust methods as well as detect outliers. The implemented objects and functions can be applied by both practitioners and researchers.

The main areas that will be covered in the book include theories and application of Nonlinear Robust Regression. In both parts the classic and robust aspects of nonlinear regression will be discussed. Outlier effects is among the main focus in the book.