# Re: [R] Increasing precision of rgenoud solutions

From: Paul Smith <phhs80_at_gmail.com>
Date: Thu, 10 May 2007 21:56:49 +0100

Thanks a lot, Jasjeet. That is it.

Paul

On 5/10/07, Jasjeet Singh Sekhon <sekhon_at_berkeley.edu> wrote:
>
> Hi Paul,
>
> I see. You want to increase the population size (pop.size)
> option---of lesser importance are the max.generations,
> wait.generations and P9 options. For more details, see
> http://sekhon.berkeley.edu/papers/rgenoudJSS.pdf.
>
> For example, if I run
>
> a <- genoud(myfunc, nvars=2,
> Domains=rbind(c(0,1),c(0,1)),max=TRUE,boundary.enforcement=2,solution.tolerance=0.0000001,
> pop.size=6000, P9=50)
>
> options("digits"=12)
>
> I obtain:
>
> #approx analytical solution
> sum(c(0.707106781186548,0.707106781186548))
> [1] 1.41421356237
>
> #genoud solution
> #a\$value
> [1] 1.41421344205
>
> #difference
> a\$value-sum(c(0.707106781186548,0.707106781186548))
>
> [1] -2.91195978441e-09
>
> If that's not enough precision, increase the options (and the
> run-time). This would be faster with analytical derivatives.
>
> Cheers,
> Jas.
>
> =======================================
> Jasjeet S. Sekhon
>
> Associate Professor
> Travers Department of Political Science
> Survey Research Center
> UC Berkeley
>
> http://sekhon.berkeley.edu/
> V: 510-642-9974 F: 617-507-5524
> =======================================
>
>
>
> Paul Smith writes:
> >Thanks, Jasjeet, for your reply, but maybe I was not enough clear.
> >
> >The analytical solution for the optimization problem is the pair
> >
> >(sqrt(2)/2,sqrt(2)/2),
> >
> >which, approximately, is
> >
> >(0.707106781186548,0.707106781186548).
> >
> >The solution provided by rgenoud, with
> >
> >solution.tolerance=0.000000001
> >
> >was
> >
> >\$par
> >[1] 0.7090278 0.7051806
> >
> >which is not very precise comparing with the values of the
> >(analytical) solution. Is it possible to increase the degree of
> >closeness of the rgenoud solutions with the analytical ones?
> >
> >Paul
> >
> >Paul Smith writes:
> > > Dear All
> > >
> > > I am using rgenoud to solve the following maximization problem:
> > >
> > > myfunc <- function(x) {
> > > x1 <- x[1]
> > > x2 <- x[2]
> > > if (x1^2+x2^2 > 1)
> > > return(-9999999)
> > > else x1+x2
> > > }
> > >
> > > genoud(myfunc, nvars=2,
> > > Domains=rbind(c(0,1),c(0,1)),max=TRUE,boundary.enforcement=2,solution.tolerance=0.000001)
> > >
> > > How can one increase the precision of the solution
> > >
> > > \$par
> > > [1] 0.7072442 0.7069694
> > >
> > > ?
> > >
> > > I have tried solution.tolerance but without a significant improvement.
> > >
> > > Any ideas?
> > >
> > > Thanks in advance,
> > >
> > > Paul
> > >
> > >
> >
>

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