ABSTRACT
There are many statistical methods of estimating parameters. Two of the more common types used in parameter estimation are linear least squares regression and nonlinear least squares regression. Both linear and nonlinear regression can be used to estimate parameters in functions in which the relationship between the dependent and independent variables is nonlinear. There are advantages and disadvantages to each method and each is more appropriate for different types of models. We will not go into the statistical theory of regression here. The theory of regression is covered in many standard texts, some of which are listed at the end of this chapter.
