Technical Report, SFB 475: Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund 2000,48
In geostatistics, spatial data will be analysed that often come from irregularly distributed sampling locations. Interest is in modelling the data_ i.e. estimating distributional parameters and then to predict the phenomenon under study at unobserved sites within the corresponding sampling domain. The method of universal kriging for spatial prediction was introduced to cover the problem of spatial trend effects. This is done by incorporating linear trend models e.g. polynomial functions of the spatial coordinates. However, universal kriging is sensitive to additive outliers. An outlier resistant method for spatial prediction is median polish kriging. Both methods have certain advantages but also some drawbacks. Here, universal kriging and median polish kriging will be combined to the robust spatial prediction method called modified median polish kriging. An example illustrates the method of modified median polish kriging along with piezometric_head data from the Wolfcampn Aquifer.