[R-sig-Geo] Handling realisations in geoRglm

Chris Barker cmbarker at ucdavis.edu
Thu Aug 31 18:22:34 CEST 2006


Dear Dr. Ribeiro and Dr. Christensen,

Thanks very much to both of you for your replies.  Your answers are a 
big help, even if the answer is no.  I'll continue my search for a 
package to analyze my data, and if realisations are ever accommodated in 
geoRglm, I'd love to revisit this.

Thanks again,
Chris


Paulo Justiniano Ribeiro Jr wrote:
> Chris
>
> I'm afraid with the current implementation the answers are no and no ...
> geoRglm cannot handle realisations as geoR does (e.g. considering
> different years as independent replications of the process).
>
> Furthermore neither geoR nor geoRglm can fit spatial-temporal models
> (with both, space and time dependence)
> RandomFields can do this but, to my knowledge, only for Gaussian data
>
> best
> P.J.
>
>
> On Wed, 30 Aug 2006, Chris Barker wrote:
>
>   
>> Dear R users:
>>
>> I want to model mosquito count data based on landcover attributes and
>> meteorological variables using a Poisson GLSM in the geoRglm package.  I
>> have monthly mosquito counts over more than 20 years with repeated
>> observations from individual trap sites over time.  I have used
>> as.geodata() to successfully read my dataset into the geodata format
>> utilized by geoR and geoRglm, including specification of the
>> realisations.  (I know the realisations have been specified correctly
>> because I can get data summaries by realisation from the geodata
>> object.)  However, after reading the packages' documentation and
>> searching the mailing lists and other sources, it seems that the
>> functions in geoRglm do not acknowledge the existence of multiple
>> realisations per site.  I see that the likfit() function in geoR has an
>> argument for realisations, but I cannot find anything similar in
>> geoRglm.  Is it possible to model data with repeated realisations from
>> the same sites using geoRglm?  If so, how can this be done and is there
>> a way to model dependence among the realisations over time?
>>
>> Thank you,
>> Chris Barker
>> Ph.D. Candidate
>> University of California, Davis
>> cmbarker at ucdavis.edu
>>
>> _______________________________________________
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>> R-sig-Geo at stat.math.ethz.ch
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>>
>>     
>
>   

-- 


Chris Barker
Ph.D. Candidate
Department of Entomology
Mailing Address: 
Center for Vectorborne Diseases
University of California
Old Davis Road
Davis, CA  95616
Phone: 530-752-0151
Fax: 530-754-6360
E-mail: cmbarker at ucdavis.edu

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