1) What manager in the mining or petroleum industry who has graduated
from college hasn't taken a serious statistics course, including covariances
and correlations?
2) Surely when starting from scratch, educating someone about
geostatistics is more intuitive using covariances? (Just my opinion so far,
speaking as a mathematician who remembers teaching basic college level
statistics to nursing majors, education majors, sociology majors, etc. And
even succeeding occasionally.)
3) I have taken two multi-day courses in geostatistics from well known
industry experts. In each class they included significant material and time
on the first day explaining/justifying variograms by showing their
mathematical relationship to spatial covariance functions. It seems that
those instructors did not trust the variogram to be more intuitive than
spatial covariance functions.
4) The two basic level introductions to geostatistics I have on my
bookshelf replicate the experience at those two classes....
Steven Zoraster
-----Original Message-----
From: Yetta Jager [SMTP:[EMAIL PROTECTED]] <mailto:[SMTP:[EMAIL PROTECTED]]>
I think part of the difficulty in the semivariogram vs. covariance war is
that modeling is subjective, and the notion of covariance has become more
intuitive for statisticians, while the notion of semivariance has become
more intuitive for geologists.
From: Isobel Clark [[EMAIL PROTECTED]]
I agree that the semi-variogram approach is easier for the non-statistician
to grasp. Difference in value is a simpler concept to grasp than
cross-product, especially when your boss wants to know the likely difference
between what you tell him and what really happens!
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