Recep kantarci wrote:
Dear ai-geostats members
When the data used has a trend, it is needed to model trend and in this
case there exists various types of kriging to apply (universal kriging,
kriging with a trend, regression kriging etc).
If this is the case, does one should use the same type of kriging or
different depending on modeling the trend using coordinates of target
variable or using other (namely, secondary or auxillary) variables such
as elevation or topography ? That is , are there a dinstinction
depending on the type of variables to model the trend while kriging?
I believe not. There's a fourth term, "kriging with external drift",
which also is the same, in my view. Some people may like to distinguish
the case where external variables are (powers of) coordinates or not,
but mathematically it's all identical.
If we were to choose a name now, maybe I would prefer "regression
kriging", but being the (newest) fourth name for an old technique, I
don't like it. We also stick to "simple" and "ordinary" kriging.
There's also the other issue of doing regression and
residual kriging separately and adding the results, which may be
coined regression kriging.
--
Edzer
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