Kriging for cut-offs and other difficult problems
Selective environmental remediation and environmental-just ice regulations require prediction of processes above a cut-off. This is an example of a nonlinear question that includes other difficult problems such as predicting transformations of the process or predicting the spatial cumulative distribution function. In this paper, we explore the notion of matching variances and covariances of a multivariate predictor with its multivariate predictand (Aldworth and Cressie, 2001). The resulting predictor has useful unbiasedness properties for prediction of nonlinear spatial functionals. Surfaces are rougher than kriging surfaces and, in a sense, represent a compromise between kriging and conditional simulation.