Traditional Ordinary cokriging sets the sum of the weights applied to the primary variable to one and the sum of the weights applied to the secondary variable to zero.The Ordinary type is the default selection. Ordinary cokriging sets the sum of the weights applied to all variables to one.This version requires working on data residuals or equivalently on variables whose means have all been standardized to zero. Simple cokriging imposes no constraints on the sum of the weights of the variables.Select the desired variation of the cokriging algorithm from the Cokriging type list. Specify the cokriging standard deviations file, cokriging type, and estimation method in the Grid Data Cokriging Options dialog. In the Grid Data dialog, specify Cokriging as the Gridding Method and click the Next button twice to open the Grid Data Cokriging Options dialog. See Kriging for more information about the interpolation method. For cokriging to be effective, the two variables must be correlated and the primary variable must be undersampled with respect to the secondary variable. Cokriging is a geostatistical gridding method that uses a densely sampled second correlated variable to improve the estimation of a primary variable.
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