S-PLUS provides two functions to fit nonlinear models that do not conform even to the partially linear paradigm of generalized linear models. These are ms() for arbitrary minimization problems where the objective functions is a sum of similar terms, and nls() for conventional nonlinear least squares estimation of normal nonlinear regression models.
In this brief introduction we only consider the nonlinear regression function nls() and leave ms() for the reader to pursue as needed.