[R] High dimensional optimization in R

[Ruben]

Hi,

Sarah Goslee (jn reply to  Basic optimization question (I'm a rookie)):  
"R is quite good at optimization."

I wonder what is the experience of the R user community with high 
dimensional problems, various objective functions and various numerical 
methods in R.

In my experience with my package CatDyn (which depends on optimx), I 
have fitted nonlinear models with nearly 50 free parameters using 
normal, lognormal, gamma, Poisson and negative binomial exact 
loglikelihoods, and adjusted profile normal and adjusted profile 
lognormal approximate loglikelihoods.

Most numerical methods crash, but CG and spg often, and BFGS, bobyqa, 
newuoa and Nelder-Mead sometimes, do yield good results (all numerical 
gradients less than 1)  after 1 day or more running in a normal 64 bit 
PC with Ubuntu 16.04 or Windows 7.

Ruben

-- 

Ruben H. Roa-Ureta, Ph. D.
Consultant, ORCID ID 0000-0002-9620-5224
Marine Studies Section, Center for Environment and Water,
Research Institute, King Fahd University of Petroleum and Minerals,
KFUPM Box 1927, Dhahran 31261, Saudi Arabia
Office Phone : 966-3-860-7850
Cellular Phone : 966-540026401