>From: Spencer Graves The correlation between the predictions from your >two model fits is 0.95. This suggests to me that the differences between >the two sets of answers have little practical importance, and anyone who >disagrees may be trying to read more from the results than can actually be >supported by the data. It should be fairly easy to select the apparent >"best" from among several such answers being the one that had a higher >log(likelihood). This pushes me to prefer "fit.bar" with a log(likelihood) >of -32.31 to "fit.foo" with -33.05. > > I agree that the differences are somewhat disturbing, but you are >dealing with the output from an iterative solution of a notoriously >difficult problem, and the standard wisdom is that it is wise to try >several sets of starting values. By modifying the order of the >observations in the data.frame, you have effectively done that.
Spencer, thank you for setting my mind at ease. Still, I suspect there's a bug here, as the convergence procedure halts entirely when I sort the data yet another way. See http://article.gmane.org/gmane.comp.lang.r.general/53559 . Also, I wonder if it's appropriate to simply cherry-pick a model based on logLik, since there's no final test that of goodness of fit that happens on independent data after one has picked a model in this way. ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html