Good question, I'll include r-sig-geo as well.
actually the prediction equations you end up with are kind of funny, and
I've never seen them written out. Two different covariance matrices
being inversed.
Package gstat can do the two-step approach: global BLUE, then simple
kriging of
On Wed, 20 Aug 2008, Samuel Field wrote:
List,
Is it possible to decompose the variance of an outcome into trend,
signal and noise components using a SAR model - analogous to what one
would get with an OLS model? This doesn't seem to be straight forward.
With OLS, we decompose Y into two
I would add Ordinary Least Squares (It may be the same as your SS), Weighted
Least Squares, Maximum Likelihood and Restricted Maximum Likelihood.
These four methods are available in the function likfit of the package geoR.
I've been using it a little bit and I think sometimes one method works
Dear Radim, Edzer,
I was thinking about the same problem few years ago (I assume that you work
with auxiliary maps and
not only coordinates).
I think (have a feeling) that local and global Universal kriging should be
treated as two things
(especially if you put a very narrow search radius).
Hello everybody!
For sure it is very simple, but I can't find the way.
How could I obtain the numerical values of a experimental semivariogram or
variogram? Is it any function that makes this in geoR or gstat (or out of them)?
Thanks!
Pilar
Mª Pilar Tugores Ferrà
Becaria FPI - PhD Student
