Dear Jean-Philippe,

Your question is somewhat puzzling. In fact, in all rigor
factorial kriging is already a kind of cokriging since
you are estimating a variable (i.e. spatial component)
from another variable (raw measurements).
Are you trying to estimate regionalized factors, that
is perform multivariate factorial kriging, or do you
want to filter your seimic data and use it as secondary
information to estimate another variable?
I used a similar approach in:

Goovaerts, P. 1999.
Accounting for scale-dependent correlation in the spatial prediction
of soil properties. In A. Soares, J. Gomez-Hernandez, and R. Froidevaux,
editors, geoENV II - Geostatistics for Environmental Applications.
Kluwer Academic Publishers, Dordrecht, pages 405-416.

Regards,

Pierre
<><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><>

Dr. Pierre Goovaerts
President of PGeostat, LLC
Chief Scientist with Biomedware Inc.
710 Ridgemont Lane
Ann Arbor, Michigan, 48103-1535, U.S.A.

E-mail:  [EMAIL PROTECTED]
Phone:   (734) 668-9900
Fax:     (734) 668-7788
http://alumni.engin.umich.edu/~goovaert/

<><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><>

On Mon, 31 Mar 2003, [iso-8859-1] Jean-Philippe Goyen wrote:

>
> hello ai-geostatisticians,
>
> I am trying to program factorial co-kriging for filtering of seismic amplitudes. But 
> I didn't find anywhere the algorithm or even matrix formulation of the system to 
> solve. As I am more a computer-scientist than a geostatistician, I am not sure of 
> setting the rigth system to solve.
>
> So I was just wondering if it would be correct to perform factorial kriging of my 
> two sets of data (as I could obtain decomposed variograms), and then cokrige the 
> results ? (hope my question has a sense).
>
> Thank you very much for any advice or reference.
>
> Jean-Philippe Goyen
>
>
>
> ---------------------------------
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