Thanks everyone for the quick and accurate responses.
My original question
Can you please help me decipher the following message from S+ spatial
> elev.krige.gaus <- krige(Z~loc(X,Y), data = elev, covfun=gauss.cov,
+ range = 90, sill = 115)
Error in .Fortran("ssukrige",: Covariance matrix is not positive
Covariance matrix is not positive definite in: .Fortran("ssukrige",
I can get krige to work for a spherical model, but not for the
gaussian. Is this a problem with a large matrix (over 900 elements in
the elev data set) in S+?
The solution (2 parts) provided by Stephen Kaluzny, J. Kern, K.
Malakhanow, D. Allard, B. Ripley, A. Riding, D. Myers, and C.D. Lloyd:
The first is that since many of my values are close together S+ is
treating them as in the same area. Therefore I needed to increase the
number of values used in the covariance function interpolation. It turns
out that the "nc = " parameter controls this. I increased from the
default (1000) to 500000 (the most allowed by the default memory
Concurrent with this I also added a nugget value of 3 to my model. As
Donalsd Myers puts it:
"However the problem with the Gaussian is a further complication. If you
examine the graph of a Gaussian you see that it has values that are
zero (assuming no nugget) for a considerable distance (relative to the
range) hence when one uses the usual kind of a search neighborhood,
only the nearest data locations, this can result in lot of variogram
in the kriging matrix that are nearly zero. This likely results in an
ill-conditionned matrix and depending on how they attempt to solve the
system of equations it may not have a unique solution."
But just increasing my nugget to 3 was not sufficient, therefore I
increased the nugget AND the nc value. Hope this helps ppl in the
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