Kriging With Nonparametric Variance Function Estimation
Jean D. Opsomer, D. Ruppert, M. P. Wand, U. Holst, O. Hussjer
February 1998 [98-WP 188]
The authors propose a method for fitting regression models to data that exhibit spatial correlation and heteroskedasticity. A combination of parametric and nonparametric regression techniques is used to iteratively estimate the various components of the model. The approach is demonstrated on a large dataset of predicted nitrogen runoff statistics from agricultural land in the Midwest and Northern Plains.
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