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By 'Kriging Technique' we denote a class of interpolators based on a stochastic approach.
There is a large array of Kriging techniques, sometimes obscured by cumbersome notations and mathematics. All these different Kriging techniques have a very simple and common line: they are all regression techniques and differ only by the particular set of functions of the data which are combined into an estimator. A unique advantage of the Kriging interpolation method is its ability to quantify the reliability of prediction, to provide an estimate plus a confidence interval.
Basic
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Idea of Kriging
The basic idea of the different Kriging methods is the same. If x denotes a point in space and Z
(x) is a function of x which is known in the n observation points x1, x2, .., xn, we look for an estimate Z*(x0) of Z(x0) in an non-measured location of the form:
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