Geostatistics with Applications in Earth Sciences pp 125-138 | Cite as

# Kriging Variance and Kriging Procedure

## Abstract

In order to derive Kriging Variance, we proceed as follows: we assume that *Z′ (x)* — the random function is defined on a point support and is second order stationary. It follows that *E[Z(x)]=m*, and the covariance, defined as *E[Z(x+h)Z(x)]−m*^{2}*=C(h)* exists. We know that *E[{Z(x+h)−Z(x)}*^{2}]*=2γ(h)*. We are interested in the mean *Z*_{ V }(*x*_{0})=*1/V∫Z(x)dx*. The data comprises a set of grade values *Z(x*_{ i }), in short *x*_{ i’ }*i=1* to *N*. The grades are defined either on point supports, core supports, etc. They could also be mean grades *Z*_{ Vi }(*x*_{ i }) defined on the supports *V*_{ i } centered on the points *x*_{ i }. It is possible that the *N* supports could be different from each other. Under the assumption of stationarity, the expectation of these data is *m*. That is, *E(Z*_{ i })=*m*.

### Keywords

Covariance Kriging Summing## Preview

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