R help - May 2009 - Constrained fits: y~a+b*x-c*x^2, with a,b,c >=0

I wonder whether R has methods for constrained fitting of linear models.

I am trying fm<-lm(y~x+I(x^2), data=dat) which most of the time gives
indeed the coefficients of an inverted parabola. I know in advance that
it has to be an inverted parabola with the maximum constrained to
positive (or zero) values of x.

The help pages for lm do not contain any info on constrained fitting.

Does anyone know how to?

Regards,
Alex van der Spek

G'day Alex,

On Wed, 27 May 2009 11:51:39 +0200
Alex van der Spek <amvds at xs4all.nl> wrote:
> I wonder whether R has methods for constrained fitting of linear
> models.
> 
> I am trying fm<-lm(y~x+I(x^2), data=dat) which most of the time gives
> indeed the coefficients of an inverted parabola. I know in advance
> that it has to be an inverted parabola with the maximum constrained to
> positive (or zero) values of x.
> 
> The help pages for lm do not contain any info on constrained fitting.
> 
> Does anyone know how to?
Look at the package nnls on CRAN.

According to your subject line, you are trying to solve what is known
as a quadratic program, and there are at least two quadratic
programming solvers (ipop in kernlab and solve.qp in quadprog)
available for R.

HTH.

Cheers,

	Berwin

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