> > Dear all, > is there a way to extract individual likelihoods from a glm/lrm object? > By individual likelihoods, I mean the likelihoods whose product give the > overall likelihood of the model. > I guess the code in the base package, used to compute the Akaike Information > Criterion may help me. > However, I couldn't figure it out, probably because I'm rather new to > likelihood theory and ML estimation ;-)
The aic function just sums the corresponding density ("d") function with log=T (except for the normal and inverse Gauss, where it is written out explicitly). Note that mle are not available for the dispersion parameter of the gamma and inverse Gauss, although this makes vary little difference in almost all cases. Thus, you just need to feed the fitted values (and, if appropriate, the dispersion estimate) into the corresponding density function without summing. Cheers, Jim > Thanks for any help/suggestion/tip, > Bruno > > ______________________________________________ > [EMAIL PROTECTED] mailing list > https://www.stat.math.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html > ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html