Nonlinear Regression
A. Ronald Gallant
The American Statistician,
May 1975, Vol. 29, No. 2., pp. 73-81.
Abstract
This article is addressed to those occasions when it is inappropriate to
use a model which is linear in the parameters to study the data. The
article presents the theory and methods of nonlinear regression by
relying on analogy with the theory and methods of linear regression, on
examples, and on Monte-Carlo illustrations rather than on formal
mathematical statements of regularity conditions and theorems.
References to this literature will, however, be provided throughout the
discussion.