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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