Hello,
I am reading some geostatisitics texts, and they
introduce random functions.
Some texts say;
A deposit D is made of a set
of random variables Z(x) which make up a random
function.
Z(x) is hence a set of possible realizations e.g. z(x)
I understand this, however in
Dear list,
Thanks for the replies about random functions and variables
Z(x,w), I thought of a
good example for w which may represent grades of a material
and Z(x,w) could
represent dollar values, if one for instance were modeling
multiple grades. Another
example may be calorific
Dear list,
this situation posed by Mr.Merks, in which spatial dependence is not
strong enough as to be useful for geostatiscs, might be rather common.
I'd like to ask to the list, what kind of estimation of reserves should
be done in this case? In the absence of spatial dependence, classical
Dear Raimon,
If the data are not spatially correlated, your variogram will be modeled as a
pure
nugget effect and all observations will receive the same weights in your block
kriging
estimation. If you perform a global block kriging (i.e. use of a single search
window), your
estimate will
