Hi Yetta
Jump in, the water is lovely! All contributions
equally valid in my e-mail box ;-)
I have to confess that I have rarely used an unbounded
semi-variogram model. In mining applications, in my
experience (which is limited to 30 years in economic
mineralisations) semi-variograms which shoot off into
the wild blue yonder are usually caused by trend,
strong anisotropy or violation of the 'homogeneity'
assumptions (stuff like faults etc or skewed
distributions).
However, the de Wijsian model is extremely popular in
Southern Africa and widely used by some major mining
houses along with simple kriging. Not my bag, but who
am I to judge?
There is an interesting paper by Cressie (not got
reference to hand, but it must be in his book
somewhere) where he treats the Wolfcamp data as an
anisotropic generalised linear model. I use a
quadratic trend surface and a spherical model for the
residuals. The final estimates are almost identical,
but the standard errors differ by an order of
magnitude.
Actually, I used that as an example in a talk in
Ireland about 10 days ago. Noel is an archetypical
ivory tower academic (and all round good guy), so I
guess we did a bit of role reversal there ;-)
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!
Keep it coming. It is your voices we want to hear, not
us border line pensioners
Isobel Clark
http://uk.geocities.com/drisobelclark
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