[R-sig-Geo] Predicted kriging variances don't match errors in cross-validation

[Roelof Coster]

Dear list,

I'm working on a local (nmax=100) space-time kriging model. I did a
cross-validation in which I made my model predict the values at 2000
randomly selected data points, based on the rest of the observations.

The results are quite good (the average error is very small, the errors are
symmetrical and the spread is not too large). However, I don't see any
correlation between the squared errors and the predicted variances. The
Kendall's tau correlation coefficient between the two is even slightly
negative. I would expect larger squared errors, on average, for data points
in which the predicted variances are large.

Should I consider this as a sign that my model is incorrect?

Best regards,

Roelof Coster

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