On 22/06/16 16:15, Nick Perpinias wrote: > Dear R-GIS users, > > I am trying to do a performance evaluation/comparison between the > covariogram and semivariogram for certain spatially correlated data. > In particular, I would like to investigate if there is a certain trade off > using either of these two tools when for example there is no trend on the > spatial field. > > Although checking the main packages for spatial statistics in R (sp, > spatstat, geoR, geoRglm, gstat) I wasn't able to find a function > calculating the experimental covariogram of a given spatial dataset.
I don't think that sp or spatstat bring you anything in this respect. gstat::variogram computes the covariogram when asked; the code that (finally) does it is here: https://github.com/edzer/gstat/blob/master/src/sem.c#L342 > > In geoRglm there is only a very specific implementation for covariogram > estimation (covariog function) and in gstat packet the variogram function > has the option of covariogram without making clear if the covariogram is > computed or extracted from the semivariogram. > > I would be grateful if you could point out an existing function of a plan > of attack for my question. I'd be interested in learning why you think this is important. > > Thank you in advance for your time and help. > > Best Regards, > > Nikos > > [[alternative HTML version deleted]] > > _______________________________________________ > R-sig-Geo mailing list > R-sig-Geo@r-project.org > https://stat.ethz.ch/mailman/listinfo/r-sig-geo > -- Edzer Pebesma Institute for Geoinformatics (ifgi), University of Münster Heisenbergstraße 2, 48149 Münster, Germany; +49 251 83 33081 Journal of Statistical Software: http://www.jstatsoft.org/ Computers & Geosciences: http://elsevier.com/locate/cageo/ Spatial Statistics Society http://www.spatialstatistics.info
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