Hi,
I also think that transition probabilities might show a better
connection to the nature of the original variable, and mcuh less
cumbersome...
Regarding the sill problem, is it so surprising, that a de-trended
variable shows less variance than the original one? If the gaussian
variable has a
Oh, I'm not sure, but I have the feeling that, in this discussion, we
are mixing the non-conditional distribution (a.k.a. the global
distribution) with the conditional (local) one... and by the way,
dismissing confidence intervals using simple kriging variance for
gaussian distributions is
Hello Julián
Short questions, short answers:
1.- as many as you want, as far as you trust the estimation of so many
cross-covariances
2.- yes, you can. And yes, you can impose such kind of constraints. For
inequality constraints, the book of Chilès and Delfiner (1999) gives
some ideas. For
that only samples from the same
layer are used in the kriging.
In short, he believes that the spatial continuity is the same in each
layer, but the mean and variability change. Your thought on this was
the same as my initial thoughts.
Isobel
http://uk.geocities.com/drisobelclark
*/Raimon
)? Or did I grossly misunderstand something in the discussion, with
so much bogus-hocus-pocus and 5-line sentences?
thanks for the patience
Raimon Tolosana
En/na JW ha escrit:
Hello Readers,
More talk and not test. I want to know what the KWBP methodology does
with the Bre-X data. Is that too
AI-GEOSTATS
Hello Ashton,
I would suggest to do the interpolation of the probability field using a
logistic scale, to avoid getting negative estimates for some categories.
This essentially implies changing your bare zeroes (in the error matrix
below) by a suitable small number (say, the
