Abstract
Co-Kriging or Joint Estimation utilizes data from correlated variables to improve the estimation of all variables or to compensate for missing data on some variables. The general formulation of Co-Kriging in matrix form was given by the author. The matrix form emphasizes the analogy with Kriging of one variable utilizing only spatial dependence. General conditions are obtained for covariance matrix functions and variogram matrix functions. The extension to block co- kriging is delineated including the Co-Kriging variance. A simple algorithm is given for obtaining the “under-sampled” case from the general matrix formulation. Finally a method for reducing the size of the system of equations is given and a iterative method provided which allows solution of even singular systems in which entries are matrices.
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References
Journel, A. G. 1977 “Geostatistique Minier” Centre de Geostatistique Fontainebleau, 737 p.
Myers, D. E. 1981 “Joint Estimation of random functions: the matrix form” Research Report, Department of Mathematics, University of Arizona 32 p.
Myers, D. E. 1982 “Matrix Formulation of Co-Kriging” Mathematical Geology, Vol. 14, No. 3, 249–257.
Myers, D. E. 1983 “Estimation of Linear Combinations and Co-Kriging” to appear in Mathematical Geology Vol. 15, No. 5
Myers, D. E. 1983 “On solving large scale linear Systems”, submitted for publication.
Tanabe, K. 1971 “Projection method for solving a singular system of linear equations and its application”, Numerische Math. 17, 203–214
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© 1984 D. Reidel Publishing Company
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Myers, D.E. (1984). Co-Kriging — New Developments. In: Verly, G., David, M., Journel, A.G., Marechal, A. (eds) Geostatistics for Natural Resources Characterization. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-3699-7_18
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DOI: https://doi.org/10.1007/978-94-009-3699-7_18
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-8157-3
Online ISBN: 978-94-009-3699-7
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