It can fit such a model. On 07/15/2013 10:19 PM, Moshood Agba Bakare wrote: > Thanks. What about gstat package? > > Moshood > > > On Mon, Jul 15, 2013 at 12:51 PM, Paulo Justiniano Ribeiro Jr < > paulo...@c3sl.ufpr.br> wrote: > >> likelihood based methods and full kriging neighbourhood in some (or most) >> of geoR functions are not suitable for such data size >> >> >> 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 >> VOIP: (+55) (41) (3361 3600) 1053 1066 >> Fax: (+55) 41 3361 3141 >> e-mail: paulojus AT ufpr br >> http://www.leg.ufpr.br/~**paulojus <http://www.leg.ufpr.br/~paulojus> >> >> >> On Mon, 15 Jul 2013, Moshood Agba Bakare wrote: >> >> Dear All, >>> Please which of these packages - gstat and geoR is better for fitting >>> spatial covariance structure model for spatial data with 20,000 >>> observations. Kindly recommend any other package you think can fit such >>> model. >>> >>> Thank you. >>> >>> Moshood >>> >>> [[alternative HTML version deleted]] >>> >>> ______________________________**_________________ >>> R-sig-Geo mailing list >>> R-sig-Geo@r-project.org >>> https://stat.ethz.ch/mailman/**listinfo/r-sig-geo<https://stat.ethz.ch/mailman/listinfo/r-sig-geo> >>> >>> >> > > [[alternative HTML version deleted]] > > _______________________________________________ > R-sig-Geo mailing list > R-sig-Geo@r-project.org > https://stat.ethz.ch/mailman/listinfo/r-sig-geo >
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