Fits a nonlinear least squares model to data. In contrast
to linear models, all the parameters (including linear ones)
need to be named in the formula. The function returned
simply contains the formula together with pre-assigned
arguments setting the parameter value. Variables used in the
fitting (as opposed to parameters) are unassigned arguments
to the returned function.