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

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