[R] Constrained Log-Likelihood with SQP Solver
wuertz at itp.phys.ethz.ch
Tue Dec 13 14:18:16 CET 2005
I'm searching for somebody who can support me or even likes to
me in setting up an R-package for "constrained maximim log-likelihood"
For example fitting the parameters of a MA(1)-APARCH(1,1) model for a
of 17'000 points (e.g. the famous Ding-Granger-Engle mode) takes about
with the existing optimization algorithms available under R.
Modern state of the art algorithms, like SQP algorithms as implemented
Matlab, Ox, take about a few seconds. I tested this finding with a free
SQP solver written in FORTRAN under R and found these results confirmed. I
got the results in a few seconds instead of a few minutes!
Now I'm looking for a collegue who has the experience in implementing
Optimization Code in R, calling the objective function and optionally
hessian from R functions. I have already inspected a lot of Fortran, C,
and R sources
from the base package, but I didn't succeed so far with a reasonable effort.
Many thanks in advance
More information about the R-help