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geoR questions

Mar?a

I will try to answer some of your questions.
Ohters will depend on the intended resulkts and may not be suitable for 
discussions hers.
geoR (and "standard" geostatistical practices)
assumes data with are at least nearly normally distributed
(maybe after transformation)
Counts or binary data can be modelled by other models/alternatives.
An alternative for Poisson and Binomial data is implemented in geoRglm 
package
cross-validation is **one of the methods** for judging or comparing models
based on comparing observed versus prediced values.
geostats literature is quite extensive on this topic
In my view anisotropy parameters are higly uncertain for most applications
and should be considered specially if you have good reasons to do so.
Adittionally you can compare fitted models with and without anisotropy to
assess the  tis relevance
according to the convergance criteria in the optimization functions used
and the associated methids.
The default is optim() with L-BFGS-B but others can be set
see ?optim, ?nlminb
image() methods in geoR (as for persp and contour) have a "values"
argument which can point to the kriging variances.
See exemples in ?image.kriging and also in the tutorials
available at geoR page (www.leg.ufpr.br/geoR)
dependes on the model but in general in geoR the same as you variable 
being modelled (this will depend if you have set a trabsformation 
parameter for the data)
Paulo Justiniano Ribeiro Jr
LEG (Laboratorio de Estatistica e Geoinformacao)
Universidade Federal do Parana
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  ufpr  br
http://www.leg.ufpr.br/~paulojus