Sorry, I can now see why I needed to provide more information. I am trying to use simulation to estimate a likelihood function that cannot be evaluated explicitly: a multinomial probit model with a spatail autocorrelation parameter for each latent dependent variable. "myfunction" generates a single latent observation (for all latent dependent variables less one) for a parameter guess. Clearly, I need to do this many times to get an accurate estimate of the likelihood. Is a loop the best way to do this? Thanks much, Michael J. Roberts Resource Economics Division, PMT USDA-ERS 202-694-5557
Prof Brian D Ripley <ripley at stats.ox.ac.uk> 01/29 1:16 PM >>>
On Mon, 29 Jan 2001, Michael Roberts wrote:
Hello, Is there a fancy way I can use a function (like apply) to avoid a the follwoing loop, or otherwise make this more efficient? It fills a 3-d array, one matrix at a time. "nsize" is big, and efficiency is important. for (i in 1:nsize) simy[,,i] <- myfunction(p1,p2, ...)
You will need to tell us a lot more. At present it appears that you are doing the same calculation nsize times, which is of course easy to avoid. Avoiding loops in R is by no mean always useful or effective. There are myths about that go back to long-forgotten versions of S, in which for loops were very much to be avoided. Up to a point *vectorization* is worthwhile, the point being where handling large vectors becones expensive.
Brian D. Ripley, ripley at stats.ox.ac.uk Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272860 (secr) Oxford OX1 3TG, UK Fax: +44 1865 272595 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._