Residual diagnostics for variogram fitting

The variogram cloud is increasingly employed in geostatistics both as an exploratory tool as well as for variogram fitting. Unfortunately in its pure form the variogram cloud cannot be effectively used to assess the fit of a corresponding parametric variogram model. This is due to the fact that its entries are highly correlated and heteroscedastic (and possibly distorted by anisotropy). We propose fitting of a model by feasible generalized least squares, suggest some diagnostics for assessing the fit and identifying potential outliers. For illustrative purposes we apply them to an example data set of chloride concentrations in the Sudliche Tullnerfeld in Austria. An R-package called vardiag for the interactive exploration of the proposed diagnostics was provided. (C) 2004 Elsevier Ltd. All rights reserved.