AI-GEOSTATS: Re: observations with a known standard deviation
- Søren Lophaven writes:
> Some time ago I asked the following question:In addition the the quite helpful responses you received, you might
> I am currently working with spatial interpolation of geophysical
> data. Each observation is associated with an individual and known
> standard deviation. How should this infomation be incorporated if
> I want to use ordinary kriging for interpolation ??
also want to take a look at the following paper:
Craig A. Schultz et al. (1998), "Nonstationary Bayesian Kriging: A
Predictive Technique to Generate Spatial Corrections for Seismic
Detection, Location, and Identification", Bulletin of the
Seismological Society of Amercia, Vol. 88, No. 5, pp. 1275-1288.
These authors consider a predictor that must perform robustly in
areas of extrapolation as well as interpolation, based on sparsely
sampled data with differing degrees of measurement error. They
work with the covariance matrices rather than semivariograms, and
they apply a normalized weighting function to introduce a Bayesian
damping factor into the kriging estimator.
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