Hello,
Further information regarding my previous email, I illustrate by means
of an example.
e.g a variogram may be computed from data;
Lag(m) SemiVariogram Number of values Coefficient of Variation
2 20 100
5%
4 40 200
3%
6 60 200
5%
8 60 200
7%
Another variogram may be calculated within a different region;
Lag(m) SemiVariogram Number of values Coefficient of Variation
2 20 100
25%
4 40 200
30%
6 60 200
28%
8 60 200
30%
In both cases a well shaped variogram has been computed to which a
spherical model could be fitted.
However the coefficient of variation is much different for the variogram
points for the two cases.
In the first case the coefficient of variation for each sample point is
fairly low, so we could assume that the variogram is a good
representation of the underlying dataset considering that we have taken
a few random samples from an underlying large population.
In the second case however the Coefficient of Variation is considerably
higher so we would wonder how much any spatial model produced from
this variogram is smoothed using a model fitted to such a variogram.
My question was I was wondering if anyone has comments or can
suggest any research or literature on the effects of the C.V., S.D. or
variance of variogram values, and their effect on producing smoothed
models.
Regards Digby Millikan B.Eng
Geolite Mining Systems
U4/16 First Ave.,
Payneham South SA 5070
Australia.
Ph: +61 8 84312974
[EMAIL PROTECTED]
http://www.users.on.net/digbym
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