If you don't worry too much about an additive constant, then half the negative squared deviance residuals should do. (Not quite sure how weights factor in. Looks like they are accounted for.)
-pd > On 25 Aug 2020, at 17:33 , John Smith <jsw...@gmail.com> wrote: > > Dear R-help, > > The function logLik can be used to obtain the maximum log-likelihood value > from a glm object. This is an aggregated value, a summation of individual > log-likelihood values. How do I obtain individual values? In the following > example, I would expect 9 numbers since the response has length 9. I could > write a function to compute the values, but there are lots of > family members in glm, and I am trying not to reinvent wheels. Thanks! > > counts <- c(18,17,15,20,10,20,25,13,12) > outcome <- gl(3,1,9) > treatment <- gl(3,3) > data.frame(treatment, outcome, counts) # showing data > glm.D93 <- glm(counts ~ outcome + treatment, family = poisson()) > (ll <- logLik(glm.D93)) > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. -- Peter Dalgaard, Professor, Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Office: A 4.23 Email: pd....@cbs.dk Priv: pda...@gmail.com ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
