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If we compute two seperate variograms for the same type of measurement, but the areas which they cover overlap, is there a logical way (or does it even make sense) to combine the two variograms?

Obviously, in this situation I am looking for a solution other than computing a single variogram over the combined datasets.

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  • $\begingroup$ There are indeed ways to combine them, but you need to know the details of the overlap so you can figure out how many pairs are common to each lag. But since computing variograms is straightforward, one would guess you don't have those details, for otherwise you would likely have the raw data and could just compute a variogram from the combined raw data. $\endgroup$
    – whuber ♦
    Commented Aug 7, 2016 at 18:58

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