Cokriging random fields with means related by known linear combinations

Abstract

Traditional approaches to predict a second-order stationary vector random field include simple and ordinary cokriging, depending on whether or not the mean values of the vector components are assumed to be known. This paper explores a variant of cokriging, in which the mean values of the vector components are related by linear combinations with known coefficients. Equations for the cokriging predictor and for the variance-covariance matrix of prediction errors are presented. A set of computer programs is provided and illustrated with applications to mineral resources evaluation, in which the proposed cokriging variant compares favorably with traditional approaches.