Hello, I would like to estimate the parameters of multinomial GLMMs by maximum likelihood. Or at least, I would like to compute the likelihood of a given set of parameters. In the case of multinomial GLMs (i.e. with discrete nominal response variable), I would use a command like
> library(VGAM) > summary(vglm(as.factor(output) ~ var1, data = mydataset, > family="multinomial")) In the case of binomial GLMMs (i.e. with binary response variable), I would use a command like > library(lme4) > summary(glmer(as.factor(output.bin) ~ var1 + (1 | cluster1), data = > mydataset.bin, family = binomial)) How to compute the likelihood in multinomial GLMMs, then ? (They can be seen as an extension of multinomial GLMs with random effects, or as an extension of binomial GLMMs to polytomous data). Or even better: how to estimate the parameters by maximum likelihood ? Thanks for your help, JB -- View this message in context: http://r.789695.n4.nabble.com/Multinomial-GLMMs-in-R-tp2955987p2955987.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list 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.