Thanks for this guidance.
In light of your advice I have reduced the titanic to a dingy by reducing the
size of my sample to just 100 instances, making this an optimisation of 100
parameters. I am, however, seeing similar output when I output the function
value at each evaluation. This is the tail of the information in the optout
results structure
[1] 70104.64
[1] 70104.67
[1] 70104.64
[1] 70104.67
[1] 70104.64
[1] 70104.67
[1] 70104.64
[1] 70104.66
[1] 70104.64
[1] 70104.66
> optout
$par
[1] 1.003 1.003 1.003 1.003 1.003 1.003 1.003 1.003 1.003 1.003 1.003 1.003
[13] ...
[97] 1.003 1.003 1.003 1.003
$value
[1] 70104.4
$counts
function gradient
501 NA
$convergence
[1] 1
$message
NULL
Can you or anyone suggest another optimisation routine I can use? I initially
coded this into EXCEL and used the solver addin to do an optimisation of 200
parameters. R was my attempt to increase this number of parameters. I do not,
unfortunately, have any derivative information.
--
Stephen Clark,
Second year PhD, School of Geography
Tel : 0113 343 6707
Email : g...@leeds.ac.uk
Web : http://www.geog.leeds.ac.uk/people/s.clark
-----Original Message-----
From: Prof J C Nash (U30A) [mailto:nas...@uottawa.ca]
Sent: 13 July 2013 13:07
To: r-help@r-project.org; Stephen Clark
Subject: [R] Optimisation does not optimise!
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
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