I wondered was people on this list felt about this article: http://www.voxeu.org/index.php?q=node/2363 which talks about the problems of obtaining sound answers in numerical optimisation in settings such as MLE or NLS. -- Ajay Shah http://www.mayin.org/ajayshah ajayshah at mayin.org http://ajayshahblog.blogspot.com <*(:-? - wizard who doesn't know the answer.
Ajay Shah <ajayshah <at> mayin.org> writes:> > I wondered was people on this list felt about this article: > http://www.voxeu.org/index.php?q=node/2363 > which talks about the problems of obtaining sound answers in numerical > optimisation in settings such as MLE or NLS.It seems perfectly reasonable (it says that lots of real-world optimization problems have multiple maxima and rough surfaces and that a variety of stochastic global optimization techniques like simulated annealing, genetical algorithms, differential evolution, etc., are useful) but nothing desperately new. R does have some tools (genoud package, method="SANN" in optim) for heuristic optimization etc. but (perhaps because they generally require a lot of tuning/fiddling) they aren't as generally available and polished as the optimization methods that assume a smooth/unimodal surface ... Ben Bolker
Ajay, Bayesm deals with this very issue in choice modelling (a form of econometric modelling as outlined in the article). I think those guys (the developers of Bayesm) and the apprach they recommend for navigating the likelihood function through a bayesian approachs makes a lot of sense to me, in fact I think they are really onto something amazing here. I am still trying to get the execution side of things from this package adequately sorted for my own purposes. Paul> Ajay Shah <ajayshah@mayin.org> wrote: > > I wondered was people on this list felt about this article: > http://www.voxeu.org/index.php?q=node/2363 > which talks about the problems of obtaining sound answers in numerical > optimisation in settings such as MLE or NLS. > > -- > Ajay Shah > http://www.mayin.org/ajayshah > ajayshah@mayin.org > http://ajayshahblog.blogspot.com > <*(:-? - wizard who doesn't know the answer. > > ______________________________________________ > 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.