On 03/02/2011 07:21 AM, Alex Lechner wrote: > Hi, > > This might be an easy question for many of you. > > In the literature on co-kriging I have noticed that co-kriging is often used > when the co-variable is more abundant than the target variable. Is this an > assumption that must be met when conducting co-kriging?
No. However, if the interest is in the primary variable, one or more secondary variables that are not sampled more densely than the primary variable improve the prediction usually very little, when compared to ordinary kriging. When one uses cokriging because one is interested in multivariable prediction, meaning that not only the predictions and prediction errors of all p variables are of interest, but also their prediction error covariances, cokriging is needed anyhow, irrespective differences in abundance. > Regards, > Alex Lechner > > > [[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 Weseler Straße 253, 48151 Münster, Germany. Phone: +49 251 8333081, Fax: +49 251 8339763 http://ifgi.uni-muenster.de http://www.52north.org/geostatistics e.pebe...@wwu.de _______________________________________________ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo