realized nobody replied to your question (sorry for have added confusion here).
don't see any objection in applying any interpolator to probability
However, you should better use exact interpolators to
avoid getting probabilities of occurences > 1 (or smaller than
I try to reformulate
When performing direct (i.e. without crossvariogram)
indicator kriging, practically we interpolate probability values by means of
ordinary kriging. These probability values could represent the probability of
occurrence of some category or the probability to overcome some threshold.
My question is: is there anything wrong to interpolate these probability
values with other interpolating algorithm like, for example natural neighbor
In my opinion is all ok ..... considering also that we
have no problem of order relation violations.
Again, this technique is
applied only for a preliminary data analysis
Then a short consideration
directed about the importance of boundaries:
"My personnal feeling about the distinction between using a
classification algorithm or a regression one is the importance you put on the
boundaries.If you look for smooth boundaries, with uncertainty estimations,
etc., then a regression algorithm (like indicator kriging) is certainly a good
Well, if you use fuzzy classification the boundaries