Isobel,
I agree with you that no estimation is needed if we have the population,
and that's what I said in the beginning of my last discussion. I'm saying
that when variance and sill in a population doesn't match, I'll have
concern when I have to use sill in a sample to estimate the
population var
Digby
The variance/sill relationship is theoretical and does
not depend on the layout of the samples, regular or
clustered. Since the sill only uses pairs where
samples are uncorrelated from one another, the
clustering is irrelevant.
It does depend on the distribution of the samples
values being
Meng-Ying,
Even if your population variance and sill do not match identically,
the sample sill should still be a better estimate than the sample variance,
when you consider the amount of clustering which occurs in sampling.
Digby
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On Thu, 9 Dec 2004, Digby Millikan wrote:
> Meng-Ying,
>
> Even if your population variance and sill do not match identically,
> the sample sill should still be a better estimate than the sample
variance,
> when you consider the amount of clustering which occurs in sampling.
>
> Digby
>
All righ
Meng-ying,
I did mean the clustering of locations, if the sample is evenly and or
randomly
spread your s^2 estimate will be no problem, it's when the data is clustered
in
locations I believe removal of these data improves the estimate, the less
clustering
the less improvment, the higher the clus
Meng-ying,
Sorry I don't have time to process the data yet, but a summary so far,
is that geostatisitcs was originally developed in the mining field, and
for the application of mineral resource assesment with which I am involved
where sampling patterns are generally clustered and the use of the sil
Like Isobel mentioned, the sill only uses pairs where samples are
uncorrelated from one another, and in this case the clustering is
irrelevant.
And I totally agree with that. The crucial thing, Digby, is that you want
to make sure the variance estimated reflects the characteristic of what
you actu
Isobel,
Thankyou, in relation to Colins work then the variance
may be estimated from the sill of the variograms for
the two orebodies and if the two orebodies had lognormal
distributions, they may have a different mean and variance,
but may still display the proportional effect, i.e. similar
coeff
