Do you have non-spatial control data? i.e. have you
measured resistivity at single locations at a number of frequencies? This should
help show you whether the effect you are seeing on the spatial data set is due
to uncreased accuracy with longer frequency (as suggested by Colin Badenhorst,
Title: Message
Ciao
Sebastiano,
I
realized nobody replied to your question (sorry for have added confusion here).
I
don't see any objection in applying any interpolator to probability
values.
However, you should better use exact interpolators to
avoid getting probabilities of
Hi,
In fact, as long as the weights are all positive and sum up to one, your
interpolated probability
will always be between 0 and 1; so you should be all right..
The approach proposed by Sebastiano is similar to median indicator kriging in
the sense
that the weights assigned to the
Dear Pierre and Gregorie
Thank you for your help .
Concluding (considering that natural neighbor method should be a convex and
an exact interpolator) it seems that the approach has not side effects !!
Sincerely
Sebastiano
At 17.19 05/09/2005, you wrote:
Content-Class:
Dear list members
Whenstudied on alog-transformed variable and intended toconstruct prediction intervals, whichoption should be followed? Why?
1) construct prediction interval first, back-transform later.
OR
2) back-transform first, construct prediction interval later.
Thanks in advance
Recep
What back-transform would you use for (1)? I use Sichel's theory, which produces prediction intervals for the lognormal back transform. Download any one of my lognormal kriging papers from http://uk.geocities.com/drisobelclark/resume (late 1990s, various audiences).
IsobelRecep kantarci [EMAIL
