gstat: Cokriging with unusual neighbourhood choice - is this possible?
-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Dear Ralph, I guess you'd need to define three variables, concA, precA and precB. Then, you can let precA and precB have different neighbourhood specs, but make them statistically "identical" by specifying the same variograms for precA and precB as well as for its cross variogram, and use the merge option to have them share a single mean value. (see ?gstat ; there's an example of this in demo(pcb) ).
On 07/23/2013 11:21 AM, Ralph Mettier wrote:
I'm looking at two variables, concentration and precipitation, measured at two networks of stations: network A measures both variables at few (~30), widely spaced stations network B measures only precipitation at many (~1800) densely spaced stations a decent correlation between the two variables is expected, making cokriging an attractive choice. Ordinary cokriging in gstat works, using only concentration from network A and precipitation only from network B. However, for quality assurance, I am trying to reproduce previous results obtained using a different, commercial, geostatistics tool. Currently, I am using nmax (and maxdist) to control the points in the neighbourhoods (16 concentration and 32 precipitation), but what I would ideally need to do is the following: For concentration, the neighbourhood should contain the 16 nearest measurements from network A, as is the case now. For precipitation, the neighbourhood should contain the 16 nearest measurements from network B and the 16 nearest measurements from network A. This doesn't seem possible using the 'nmax' option in gstat. I have tried splitting concentration and precipitation from network A into two seperate gstat objects and then using cokriging with three variables, but the results are unsatisfying and I'm fairly certain this is not the way to go. Any hints or pushes in the right direction would be greatly appreciated. Best Regards Ralph [[alternative HTML version deleted]]
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