AI-GEOSTATS: kriging and radial basis functions
- hello all,
There are some similarities between interpolation-algorithms based on radial
basis functions and kriging. I am not sure whether i understood it right or
not. May be someone can help me and tell me if i am on the right way:
In kriging i get optimal weights (w) for data points by solving the matrix:
C = w * D
C= covariance matrix between data points
D = covarince-matrix between data points and grid node
using interpolation based on radial basis functions i just do the same
except that i have to replace variogram-dependend covariance-matrices C and
D by one of the distance-dependend rbf-functions ?
Bayerisches Geologisches Landesamt
(Geological Survey of Bavaria)
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