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Wikipedia says:

In applied statistics, regression-kriging (RK) is a spatial prediction technique that combines a regression of the dependent variable on auxiliary variables (such as parameters derived from digital elevation modelling, remote sensing/imagery, and thematic maps) with kriging of the regression residuals.

What is the exact reason of kriging of the residuals in regression-kriging?

gung - Reinstate Monica
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Charlie
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    The several answers at http://stats.stackexchange.com/questions/35510 appear to address this fully. Gavin Simpson's answer (the accepted one) directly talks about residuals. My answer there discusses specifically what goes wrong, and how it goes wrong, when you try to krige data that have a strong underlying trend. – whuber Feb 26 '16 at 17:12

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