lgj200306 <lgj200306@...> writes: > > Thaks David very much, but how can I > improve my model? Should I change my likelihood function > or do some thing else? > Best wishes for all list members!
Your choices are: (1) if the final result looks sensible, and none of the final predicted values lead to NA/NaN results, you can *probably* ignore these warnings (2) depending on your model, you may be able to bound some of the parameters (e.g. using method="L-BFGS-B" and specifying lower/upper values) *or* fit them on a different scale (e.g. the log scale) to prevent zero/negative predicted values of lambda (predicted values of zero will be OK as long as they always go with observed values of zero -- otherwise you'll get infinite (negative) log-likelihood values. There are some simple examples of bounded optimization in the ?mle2 examples ... > > At 2011-10-21 04:05:10,"David Valentim Dias" > <dvdscripter <at> gmail.com> wrote: > Should be a bad parameter like you get from dpois(1, -1) > > 2011/10/20 lgj200306<lgj200306 <at> 163.com> > Hi, all > I have a problem about the log maximum likelihood. > I want to estimate several parameters using > log maximum likelihood method (mle2() in package "bbmle" ), > and the likelihood fucton was based on poisson distribution. > When finished, there were some warnings said that: > >In dpois(x, lambda, log) : NaNs produced > Will this situation influence my result of > parameters estimating or not? If my parameters estimated have > been influenced, how can I improve my R code > or data to achieve a exact estimating? > Thanks for you attention and best wishes for all of you! > Guojun Lin > South China Botanical Garden, Chinese Academy of Science, China > Department of Renewable Resources, University of Alberta, Canada _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology