Re: [R-sig-Geo] Spatio-Temporal Kriging: Memory Issues

Hello Karim, You might want to use local kriging, as in: predicted<- krigeST(values ~ 1, data, prediction.grd, v.model, nmax = 500, stAni = 1) The nmax parameter is the number of observations that will be used for each location. The stAni is a parameter controlling whether observations that are

[R-sig-Geo] Geostatistics on geometric network

Dear list members, I'm working with electric measurements that were taken on pipelines. These are spatio-temporal data whose spatial domain is not Euclidean, because the pipelines form a geometrical network. Has any work been done before to study this kind of data? Best regards, Roelof Coster

[R-sig-Geo] Predicted kriging variances don't match errors in cross-validation

the predicted variances are large. Should I consider this as a sign that my model is incorrect? Best regards, Roelof Coster [[alternative HTML version deleted]] ___ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman

[R-sig-Geo] Local spacetime kriging

kriging in a neighbourhood is possible, how does the function determine this neighbourhood? How is distance in space compared to distance in time? Thanks! Roelof Coster [[alternative HTML version deleted]] ___ R-sig-Geo mailing list R-sig-Geo@r

[R-sig-Geo] Spacetime regression

? Thanks in advance, Roelof Coster [[alternative HTML version deleted]] ___ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo

Re: [R-sig-Geo] Spacetime regression

Thanks for the answers. I have cleaned up the data by rounding the dates to half years, and now the variogram turns out beautiful. Now I can proceed to kriging and see what I get. Best regards, Roelof Coster 2014-02-13 17:54 GMT+01:00 ldec...@comcast.net: when confronted with a large