Considering that I devised the code initially on a computer with only 8K
bytes for program and data, and it appears that your problem has 10000
parameters, I'm surprised you got any output. I suspect the printout is
the BUILD phase where each weight is being adjusted in turn by the same
shift.
Don't try to move the Titanic on a pram.
If you work out a gradient function, you can likely use Rcgmin (even
though I wrote original CG in optim(), not recommended). spg from BB may
also work OK.
This problem is near linear, so there are other approaches.
JN
On 13-07-13 06:00 AM, r-help-requ...@r-project.org wrote:
Date: Fri, 12 Jul 2013 21:22:00 +0100
From: Stephen Clark<g...@leeds.ac.uk>
To:"r-help@R-project.org" <r-help@R-project.org>
Subject: [R] Optimisation does not optimise!
Message-ID:
<928c4f7877280844b906d12d63a3f15b01145e5b5...@hermes8.ds.leeds.ac.uk>
Content-Type: text/plain; charset="us-ascii"
Hello,
I have the following code and data. I am basically trying to select individuals
in a sample (by setting some weights) to match known counts for a zone. This is
been done by matching gender and age bands. I have tested the function to be
optimised and it does behave as I would expect when the weights are changed.
However when I run the optimisation I get the following output
>optout<-optim(weights0, func_opt, control=list(REPORT=1))
[1] 27164
[1] 27163.8
[1] 27163.8
[1] 27163.8
[1] 27163.8
[1] 27163.8
[1] 27163.8
[1] 27163.8
[1] 27163.8
etc
which suggest an initial change but thereafter the optimisation does not appear
to adapt the weights at all. Can anyone see what this is happening and how to
make the problem optimise?
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
