Hi Ravi,
that's an interesting claim and N-M. Can you provide any reading matter to
support it?
Cheers,
Andrew
--
Andrew Robinson
Director, CEBRA and Professor of Biosecurity,
School/s of BioSciences and Mathematics & Statistics
University of Melbourne, VIC 3010 Australia
Tel: (+61) 0403 138
Hi John,
I wonder if you can suggest some reading material on that topic? A cursory
search of the net doesn't uncover anything obvious.
Andrew
--
Andrew Robinson
Director, CEBRA and Professor of Biosecurity,
School/s of BioSciences and Mathematics & Statistics
University of Melbourne, VIC 3010
I agree with John that SANN should be removed from optim.
More importantly, the default choice of optimizer in optim should be changed
from "Nelder-Mead" to "BFGS." Nelder-Mead is a bad choice for the most
commonly encountered optimization problems in statistics. I really do not see
a good
SANN is almost NEVER the tool to use.
I've given up trying to get it removed from optim(), and will soon give up
on telling folk not to use it.
JN
On 2020-07-22 3:06 a.m., Zixuan Qi wrote:
> Hi,
>
> I encounter a problem. I use optim() function in R to estimate likelihood
> function and the met
Simulated annealing is a probabilistic method and will do things like that. You
should probably read an introduction to the method, e.g. the Wikipedia page.
Not too unlikely, you really want to use one of the other methods in optim()
(or better still optimr from the optimx package).
(I take it
Hi,
I encounter a problem. I use optim() function in R to estimate likelihood
function and the method is SANN in the optim function.
out <-
optim(parm,logLik,method='SANN',hessian=T,control=list(maxit=500))
However, I find that each time I run the program, I will get different
values of param
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