[R] calculating the spacial autocorrelation for poisson data

Paulo Justiniano Ribeiro Jr paulojus at est.ufpr.br
Wed Jun 28 20:32:21 CEST 2006

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


Paulo Justiniano Ribeiro Jr
LEG (Laboratório de Estatística e Geoinformação)
Departamento de Estatística
Universidade Federal do Paraná
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

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
> 	[[alternative HTML version deleted]]
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