A while back, I wrote to the list/engaged in some debate with Peter Dalgaard about the mle() function in the stats4 package -- in particular, I wanted it to have a data= argument so that parameters could be estimated for different sets of data with the same minuslogl function: Peter disagreed, suggesting that a function-defining-function (e.g. something like minusloglfun <- function(data) { with(data, function(param1,param2) { [negative log-likelihood expression] }) ) was a good solution. I also had some confusion/misunderstanding about the differences between the fullcoef and coef slots within the mle object. Since then I've done a fair amount with my version of mle() [bbmle, available from http://www.zoo.ufl.edu/bolker/R/src/bbmle_0.3.0.tar.gz ] ; - confidence limits estimated by spline back-fitting (as in base mle package) OR uniroot (for higher precision/ models with non-smooth profiles) OR quadratic approximation - allows parameters to be specified as a named vector rather than a named list (so you can in principle use the same objective function for optim() or mle()) - options for profile plots - anova method for mle to produce Likelihood Ratio Test tables - AIC, BIC methods for single and multiple models - some robustness -- e.g. continues with more informative messages if (e.g.) Hessian can't be inverted or profile finds better fit I'm afraid, however, that my code is now getting somewhat idiosyncratic and spaghetti-ish -- I ran into this particularly when trying to add some options to the AIC method to allow (e.g.) small-sample corrections or calculation of AIC weights a la Burnham and Anderson. I did have the original goal of also extending mle in the direction of allowing more analytic expressions for parameters of known distributions (like Jim Lindsey's packages, but ideally (?) more robust), but I haven't gotten there yet. My main goal is to make mle a practical, robust and convenient tool for analysis ... in the long run I would love it if at least some of my changes got rolled back into stats4. Anyone out there interesting in hacking on this a bit more with me/providing some perspective on which bells and whistles are really necessary and which are unnecessary complications? cheers Ben Bolker -------------- next part -------------- A non-text attachment was scrubbed... Name: signature.asc Type: application/pgp-signature Size: 254 bytes Desc: OpenPGP digital signature Url : https://stat.ethz.ch/pipermail/r-devel/attachments/20061031/3a1dc985/attachment-0004.bin