Fitting nonlinear models: numerical techniques

Abstract

Summary Computational methods for fitting nonlinear models have developed considerably in the last decade. Statistical use of these techniques has, as yet, lagged somewhat behind. The present paper gives a critical review of current numerical techniques and relates these to some statistical needs. We emphasize the basic properties of methods of optimization and nonlinear least squares, cite some advantages and difficulties of the methods and suggest a basic library of fitting procedures. A classified bibliography is included.