Poisson Lognormal

2010/3/26 Charles C. Berry <cberry at 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