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泛协Kriging的数学模型
引用本文:韩燕.泛协Kriging的数学模型[J].东北数学,2007,23(3):272-282.
作者姓名:韩燕
作者单位:College of Mathematics, Jilin University, Changchun, 130012
摘    要:Due to its complexities in both mathematicM formulations and applications, universal co-kriging (UCK) has not been sufficiently discussed in literature. An extended and simpler matrix formulation UCK with incorporation of a polynomial variable trend is proposed in this paper. Estimators of the value and expectation of a regionMized vector taken in a point are obtained on the basis of cross-covaxiance and cross-vaxiogram, respectively. The complex expressions of co-kriging with trend are greatly simplified by introducing special matrix operations, such as Kronecker product, into the formulations. This simplification offers a feasible and easier approach for computer coding of the UCK, and helps the practitioners to use the UCK technique conveniently in real cases.

关 键 词:数学模型  协同定位  矩阵  向量
文章编号:1000-1778(2007)03-0272-11
收稿时间:2007-04-05
修稿时间:2007年4月5日

On the Mathematical Model of Universal Co-kriging
HAN Yan.On the Mathematical Model of Universal Co-kriging[J].Northeastern Mathematical Journal,2007,23(3):272-282.
Authors:HAN Yan
Institution:College of Mathematics, Jilin University, Changchun, 130012
Abstract:Due to its complexities in both mathematical formulations and applications, universal co-kriging (UCK) has not been sufficiently discussed in literature. An extended and simpler matrix formulation UCK with incorporation of a polynomial variable trend is proposed in this paper. Estimators of the value and expectation of a regionalized vector taken in a point are obtained on the basis of cross-covariance and cross-variogram, respectively. The complex expressions of co-kriging with trend are greatly simplified by introducing special matrix operations, such as Kronecker product, into the formulations. This simplification offers a feasible and easier approach for computer coding of the UCK, and helps the practitioners to use the UCK technique conveniently in real cases.
Keywords:geostatistics  co-kriging  matrix analysis  regionalized vector
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