Hi Pierre
I think that for my task factorial kriging is a little bit
too much sophisticated (nevertheless, is there any open source or
free implementation of it ??? I remember that it
is implemented in Isatis.....).
I have an exhaustive and regularly spaced data set (i.e. a grid) and I need
to calculate locally the spatial variability of the residual surface or better
I would like to calculate the spatial variability
of the high frequency component.
Here I'm lucky because I know exactly what I want
to see and what I need to filter out.
In theory, using (overlapping) moving window
averages (but here it seems better to use some more complex kernel)
one should be able to filter out the short range
variability (characterized by an
eventual variogram range within the window size???).
Seeing the problem from another perspective, in the case of a perfect
sine wave behavior, I should be able to filter out spatial
variability components with wave lengths up to the window size.
But maybe there is something flawed in my
reasoning....so feedback is appreciated!
Bye
Sebastiano
At 16.27 01/02/2010, you wrote:
well Factorial Kriging Analysis allows you to tailor the filtering weights
to the spatial patterns in your data. You can use the same filter size but
different kriging weights depending on whether you want to estimate
the local or regional scales of variability.
Pierre
2010/2/1 seba
<<mailto:sebastiano.trevis...@libero.it>sebastiano.trevis...@libero.it>
Hi José
Thank you for the interesting references. I'm going to give a look!
Bye
Sebastiano
At 15.46 01/02/2010, José M. Blanco Moreno wrote:
Hello again,
I am not a mathematician, so I never worried
too much on the theoretical reasons. You may be
able to find some discussion on this subject in
Eubank, R.L. 1999. Nonparametric Regression and
Spline Smoothing, 2a ed. M. Dekker, New York.
You may be also interested on searching
information in and related to (perhaps citing)
this work: Altman, N. 1990. Kernel smoothing of
data with correlated errors. Journal of the
American Statistical Association, 85: 749-759.
En/na seba ha escrit:
Hi José
Thank you for your reply.
Effectively I'm trying to figure out the theoretical reasons for their use.
Bye
Sebas
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