Dear list
I would like also to suggest another point:
really often there is a relationship between
topographic elevation and hydraulic head
data values; in this case an external drift approach could be useful.
Bye
Sebastiano
At 20.16 20/08/2006, Edzer J. Pebesma wrote:
Hi all,
I agree with Mario for the case where data are
abundant. For cases where data are more sparse,
or for cases where the trend is obvious, strong
and important, ignoring the trend is a waste.
A completely different case is that where the
trend is not described by coordinate
polynomials, but by external variables known for
each location, think of the variable altitude
for interpolating annual mean temperature in a
mountainous area. In this case, ignoring the trend is a waste in general, imo.
Best regards,
--
Edzer
Mario Rossi wrote:
Rajni,
you generally do not need to detrend if using
ordinary kriging (or other linear weighted
average estimator) in the interpolation case,
i.e., when the points you're estimating are
surrounded by data in (generally) all sides,
and particularly in the direction(s) of the
trend. Also, a relatively small neighborhood
should be used (generally less than the
variogram ranges; as opposed to large
neighborhoods or on at all). In such case,
universal kriging or IRF-k would not give you any additional advantage.
One possibel reference is Journel, A.G., and
Rossi, M.E., "When Do We Need A Trend Model?",
Journal of Mathematical Geology, Vol. 22, No. 8, 1989.
Another could be Rossi, M.E., and Posa, D.,
"Stationary and Nonâstationary Kriging
Applied to Dissolved Oxygen Data",
MetronâInternational Journal of Statistics, Vol. 47, No 1â4, 1989, Rome.
Cheers,
Mario
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