2010/3/26 Charles C. Berry <cbe...@tajo.ucsd.edu>: > On Fri, 26 Mar 2010, Robert Ruser wrote: > So this is the generalized linear model with a poisson family, log link, and > a Gaussian random effect in the linear predictor. > > Take a look at lme4, MASS (glmmPQL), and try searching CRAN packages for > 'glm' and 'GLM' (there are a bunch and several promise to handle random > effects, but YMMV). > Thank you. But I'm wondering how to set random effect? I have the data 'my.data': #n number count 1 0 252 2 1 163 3 2 120 4 3 95 ............................
number | exp(lambda) ~poisson(exp(lambda)) exp(lambda) ~ normal(a,b) probably I should use a formula: model.est <- glmer(number ~ 1, family = poisson(link="log"), data = my.data) but how to set random effect? I do not have predictors. Second I need to remember that for example 0 occurred 252 times. How to do it - I can do it using number = seq(number,times=count), but calculation will last longer. I would appreciate any help. Robert ______________________________________________ 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.
