Summarizing the GRF’s correlation structure

Example dataset from {geoR} for which we’ll compute semivariograms:

str(parana, max.level = 1, give.attr = FALSE)

## List of 4
##  $ east              , north             : num [1:143, 1:2] 403 502 556 573 702 ...
##  $ data              : num [1:143] 306 201 167 163 164 ...
##  $ borders           : num [1:369, 1:2] 670 664 656 650 643 ...
##  $ loci.paper        : num [1:4, 1:2] 300 648 362 410 484 ...