[R] glmmADMB: Mixed models for overdispersed and zero-inflated count data in R

From: Hans Skaug <skaug_at_mi.uib.no>
Date: Fri 17 Jun 2005 - 18:52:06 EST


Dear R-users,

Earlier this year I posted a message to this list regarding negative binomial mixed models in R. It was suggested that the program I had written should be turned into an R-package. This has now been done, in collaboration with David Fournier and Anders Nielsen.

The R-package glmmADMB provides the following GLMM framework:
- Negative binomial or Poisson responses.

The computational method is based on the Laplace approximation for integrating out the random effects, together with the option of employing importance sampling at the posterior mode of the random effects to permit arbitrarily close approximation to the exact MLE. (However for these models differences appear to be very small.)

Some of the generic convenience functions, such as predict(), fitted.values(), ... are still missing from this package, but will hopefully be added in later versions (contributions/suggestions are most welcome). Other response distributions than negative binomial or Poisson could easily be added.

Download site:

http://otter-rsch.com/admbre/examples/glmmadmb/glmmADMB.html

The package is based on the software ADMB-RE, but the full unrestricted R-package is made freely available by Otter Research Ltd and does not require ADMB-RE to run with user supplied data.

I you will find this useful,

Hans Skaug

-- 
Hans  Skaug

Department of Mathematics
University of Bergen, Norway
email: 	skaug@mi.uib.no
ph. (+47) 55 58 48 61

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Received on Fri Jun 17 18:55:52 2005

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