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317Re: AI-GEOSTATS: Sum: Spatial poisson regression software?

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  • Nicholas Lewin-Koh
    Jul 23, 2001
      Hi Ben,
      Just one more place to look is R (or Gnu Splus). There is a module on cran
      for generalized linear mixed models, which is actually a port of the
      software (beam) that was used by Clayton and Kaldor 1987 JASA. They use a
      hierarchical modeling approach and get the randome effects distributions
      using mcmc. You can also use bugs to do this as was mentioned in your

      In your question I was not sure if you wanted to model the functional
      relationship between your response and predictors or to predict unobserved
      locations. If the former then the glm approach might be the best, if the
      latter than the Gottaway and stroup approach might be better. I recall
      that articale dealt more with prediction. Another article to look at is
      diggle, tawn and moyeed (or some permutation of the names) I think the
      article is called Model Based Geostatistics and is in JRSS A or C,
      whichever is applied statistics. I don't know if they ever distributed
      software for the application, I think the MCMC procedure they used was not
      very stable.

      So the question is what are the goals of this analysis and the methods
      will follow.


      N Nicholas Lewin-Koh
      / \ Dept of Statistics
      N----C C==O Program in Ecology and Evolutionary Biology
      || || | Iowa State University
      || || | Ames, IA 50011
      CH C N--CH3 http://www.public.iastate.edu/~nlewin
      \ / \ / nlewin@...
      N C
      | || Currently
      CH3 O Graphics Lab
      School of Computing
      National University of Singapore
      The Real Part of Coffee kohnicho@...

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