Re: [R] Bounding or constraining parameters in non-linear regressions

From: Douglas Bates <dmbates_at_gmail.com>
Date: Thu 09 Jun 2005 - 00:39:20 EST

On 6/7/05, mwdavis@nist.gov <mwdavis@nist.gov> wrote:
> Dear R-Users,
>
> Being an engineer and not a statistician, my desired course of action may
> either be impossible or very simple.
>
> I am attempting to fit a non-linear model to some measured data. One term in
> the model contains a square-root, but in the course of regression, this term
> turns negative and an error occurs. I started using Micrsoft's Excel Solver,
> and then I turned to NIST's Datplot statistical package. I can constrain in
> Solver, but it violates those constraints. :) Dataplot does not have the
> capability to constrain parameters.
>
> Does R have the capability to constrain or bound parameters in non-linear
> regressions?

Sort of. If you look at the stats package in r-devel you will see that a function called nlminb has been added. This function calls optimization software from the Port package (http://www.netlib.com/port/). The Fortran code for constrained nonlinear least squares problems is included in the package but the interface code for R has not yet been written. The energetic could create such interface code by emulating that for nlminb - it's not that long.

Alternatively you could use either optim or nlminb on the function which is the residual sum of squares from your model.



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