On Fri, 26 Mar 2010, Robert Ruser wrote:
Hi R Users,
I'm going to estimate via. ML the parameters in Poisson Lognormal
model. The model is:
x | lambda ~ Poisson(lambda)
lambda ~ Lognormal(a,b)
Unfortunately, I haven't found a useful package allowing for such
estimation.
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).
HTH,
Chuck
I tried to use "poilog" package, but there is no equations
and it's hard to understand what exactly this package really does.
Using it I get the incorrect estimators.
I thing that I could use any package that allows to estimate
generalized linear mixed model, because above models is equivalent to:
x | exp(lambda) ~ Poisson (exp(lambda))
exp(lambda) ~ Normal(c,d)
Does it exist any package that can estimate it? May be you know a
package that do Gauss-Hermite quadrature for estimation or simply do
estimation for the first model?
Robert
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Charles C. Berry (858) 534-2098
Dept of Family/Preventive Medicine
E mailto:cbe...@tajo.ucsd.edu UC San Diego
http://famprevmed.ucsd.edu/faculty/cberry/ La Jolla, San Diego 92093-0901
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