Hi,
You could try using kriging with non-systematic error where you can directly
incorporate
information on the reliability of your data in the kriging system. The
technique is
described in Chiles and Delfiner's textbook.
Pierre
-----Original Message-----
From: Jose Luis Gomez Dans [mailto:[EMAIL PROTECTED]
Sent: Wed 5/11/2005 9:37 AM
To: [email protected]
Cc:
Subject: [ai-geostats] Interpolation error estimation
Hi!
I am aware that this question could easily become a
whole book, and a rather thick one at that :), but
nevermind...
I have produced an interpolation using regularised
splines. The point data that goes into the
interpolation has some measure of error associated to
it, so to a first approximation, this can be used as
an error indicator for cells of the interpolated grid
that contains one such point.
The problem arises with grid cells that have no real
data in them, as the error is a function of the error
of the surrounding points, the distance from the
surrounding points (the further you are from a sa, the
larger the error) and the error due to the
interpolation. I could try and model the error, but
there's a scale factor due to the surface presenting
different features at different scales, and it all
becomes very complicated.
So my question is, what is the best way to come up
with a grid that has a reasonable error estimation of
the interpolated surface, if we know the error of each
of the samples that went in?
Many thanks for your time and help,
JosÃ
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