Nonlinear Regression

A. Ronald Gallant
The American Statistician, May 1975, Vol. 29, No. 2., pp. 73-81.


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.