Marta
I am not familiar with the software you are using, but
it looks like your lognormal standard errors are being
back-transformed into 'raw' units. If this is the case
part of the backtransform is to multiply the 'relative
standard error' by the actual value of the estimate.
That is, if your
Dear list members,
Please advise what to do in following case:
The sparse dataset for kriging inlcudes only few
(5-6) original data points + interpolated external
data, that covering whole study area.
One of the original data points seems completly not to
fit to the main correlation line
Hi Gali,
may you not try with Radial Basis Function (Multiquadric) instead of
kriging? It's meant to be an exact interpolator, although sometimes it
doesn't fully honor your data. However, it's based on the concept of
track data which seems to me to suit the issue you mention. I employ RBF
Hi,
I am not sure i understood correctly your question. Fist of all, do
the interpolated data have come from your sparse data
interpolation? What method of interpolation did you use in this
case?
After Burrough and McDonnel, 2000, you need at least 50 points to
have reliable results through
Hi Monica,
thanks for quick reply. The interpolated data is a
different data set with is by its nature (speaking
about geological properties) should be correlated with
the sparse one.
This is a geological data over not huge area - around
20x30 kilometers. It should have at least some spatial
