R help - Mar 2010 - Poisson Lognormal

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. 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

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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> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
Charles C. Berry                            (858) 534-2098
                                             Dept of Family/Preventive Medicine
E mailto:cberry at tajo.ucsd.edu	            UC San Diego
http://famprevmed.ucsd.edu/faculty/cberry/  La Jolla, San Diego 92093-0901