Matheron used the term spherical to describe the
semi-variogram model which represents the concept of
two overlapping 'spheres of influence'. The formula is
actually the geometric calculation of the amount by
which two spheres of diameter 'a' (range of influence)
do NOT overlap when their centres a
Hi all,
Does anyboby can explain to me the origin of the variogram models: spherical
and exponential ? Why the names spherical and exponential ?
Sincerely
Charles
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I pretend to perform Universal Kriging with GSLIB, the problem is how to get
the vertical drill in bore hole data set, for use de residual variogram.
If exist other solution like use Pair-wise Relative Variogram for example.?
Other question is how to detect the best drift.
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Dear all,
to my question on weighted cross-validations, I got also a reply from Donald
Myers that has not appeared on the list and which is here forwarded.
To summarize in two words Pierre and Donald's replies : weighted
cross-validations might be an interesting step but the problem of
interpreta
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>G'day all,
>
>I reckon we need to quantify the reliability of the kriging variance map.
Because sometimes its going to be an accurate map, and other times its
going to be way off the mark.
>
>Imagine the situation when there are two maps with similar kriging
variances. However when we look at the
Hi Christopher,
I believe you forgot a key assumption, homoscedasticity.
In most situations this assumption is not realistic
and we would like the kriging variance to somehow
depend on the local variability of data.
Rescaling globally the kriging variance to
account for uncertainty about variogram
Dear Chris
Bayesian kriging is what you should use, if you want to include estimation
uncertainty into the kriging variances. Some useful references are:
Le, N.D. and Zidek, J.V. (1992).
Interpolation with uncertain covariances: a Bayesian alternative to
Kriging.
Journal of Multivariate Analysis
