Automatic Mapping in the Presence of Substitutive Errors: a Robust Kriging Approach Fournier, Baptiste Furrer, Reinhard 10.4225/03/58007202615d5 https://bridges.monash.edu/articles/journal_contribution/Automatic_Mapping_in_the_Presence_of_Substitutive_Errors_a_Robust_Kriging_Approach/3979617 Interpolation of a spatially correlated random process is used in many scientific domains. The best unbiased linear predictor (BLUP), often called kriging predictor in geostatistical science, is sensitive to outliers. The literature contains a few attempts to robustify the kriging predictor, however none of them is completely satisfactory. In this article, we present a new robust linear predictor for a substitutive error model. First, we derive a BLUP, which is computationally very expensive even for moderate sample sizes. A forward search type algorithm is used to derive the predictor resulting in a linear likelihood-weighted mean procedure that is robust with respect to substitutive errors. Monte Carlo simulations support the theoretical results. The new predictor is applied to the two SIC2004 data sets and is evaluated with respect to automatic interpolation and monitoring. 2016-10-14 05:49:52 monash:89946 1959.1/736926 SIC 2004 Automatic mapping Automatic interpolation Anomolies Outliers Radioactive contamination Environmental data Robust kriging Mapping algorithms Substitutive error 2005 collection(s) Applied GIS text journal article 1832-5505 Geography Economic Geography Geomatic Engineering not elsewhere classified