Ordinary kriging is a BLUP for random fields, but linear estimation results are often not optimal when there is a nonlinear relationship between random fields and the index set. Analytic kriging generalizes the weight coefficients in ordinary kriging to functions, thus enabling nonlinear estimation of random fields. Most commonly, given an indicator function, analytic kriging is also known as indicator kriging.
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