[R] Non-linear minimization

[Wiener, Matthew]

I have had my best luck by re-parametrizing so that I no longer needed
restrictions.  For example, if parameters must be positive, then I optimize
over parameters in log space, taking the exponential within my function.
This requires small changes to the function I'm optimizing (and the
gradient, if supplied), but, for me at least, has worked better than trying
to enforce box constraints as in L-BFGS-B.

Hope this helps,

Matt Wiener

-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Sébastien Ballesteros
Sent: Tuesday, March 08, 2005 8:24 AM
To: r-help at stat.math.ethz.ch
Subject: [R] Non-linear minimization


hello, I have got some trouble with R functions nlm(),
nls() or optim() : I would like to fit 3 parameters
which must stay in a precise interval. For exemple
with nlm() :

fn<-function(p) sum((dN-estdata(p[1],p[2],p[3]))^2)
out<-nlm(fn, p=c(4, 17, 5),
hessian=TRUE,print.level=2)

with estdata() a function which returns value to fit
with dN (observed data vactor)

My problem is that only optim() allows me to set
parameters interval with "L-BFGS-B" method but this
one doesn't work in my case.

I have heard about nls2 package (www.inra.fr/bia) but
it doesn't work on Windows.

Do you know any solutions

Thank's a lot for reading my post

Best regards

Sebastien
INA P-G ecology dpt

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