R help - Jun 2006 - calculating the spacial autocorrelation for poisson data

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Hi Ronaldo

As an exploratory analysis you can fit a glm to the data and
use variog() on the residuals to check if there is an spatial correlation.

The approach in geoRglm is more compreheensive and you can fit a 
Poisson model with spatially correlated random effects using MCMC maximum 
likelihood with likfit.glsm()

There are some examples in the geoRglm web page
http://www.daimi.au.dk/~olefc/geoRglm/

best
P.J.



Paulo Justiniano Ribeiro Jr
LEG (Laborat?rio de Estat?stica e Geoinforma??o)
Departamento de Estat?stica
Universidade Federal do Paran?
Caixa Postal 19.081
CEP 81.531-990
Curitiba, PR  -  Brasil
Tel: (+55) 41 3361 3573
Fax: (+55) 41 3361 3141
e-mail: paulojus at est.ufpr.br
http://www.est.ufpr.br/~paulojus

On Wed, 28 Jun 2006, Ronaldo Reis-Jr. wrote:
> Hi,
>
> I have some count data. I try to calculate if exist spacial
> auto-correlation. In geoR I make:
>
> variog.p50 <- variog(p50,uvec=c(1:10))
>
> but I think that the correct is using geoRglm
>
> I try:
>
> covariog.p50 <- covariog(p50,uvec=c(1:10))
>
> But it is not the same  calculation.
>
> I new in geostatistic, I'm stunding.
>
> The semivariogram I know how to interpret the output and graphics, but dont
> with covariance.
>
> Any help are welcome
>
> Thanks
> Ronaldo
>
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>
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