I was wondering if there is way to place constraints upon the "plinear" algorithm of nls, or rather is there a manner in which this can be achieved because nls does not allow this to be done.



I only want to place constraints on one of the nonlinear parameters, a, such that it is between 0 and 1. I have attempted to use a=pnorm(a*) , but then the fitting procedure becomes overcomplicated and convergence does not occur in many cases including ones I know or suspect to be useful. I have not attempted other similar functions because I want to see if there is an alternative approach although if you have an alternative to pnorm to suggest which is less complcated but maps from the real numbers to [0,1] that may be useful.



I have looked at gnm package but this is no more helpful. Any suggestions would be welcome. Basically, has the algorithm of Golub and Pereyra even been writtten to be applied with constraints in R, anywhere and by anyone? I believe it is possible to do so.



Thank you

Liam Brown

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