Kriging for large data sets: A tentative comprehensive review
Résumé
Spatial statistics for very large spatial data sets is challenging. The size n of the data set causes problems in computing optimal spatial predictors such as kriging, since its computational cost is of order n^3 . In addition, a large data set is often defi ned on a large spatial domain, so the spatial process of interest typically exhibits non-stationary behaviour. In the literature, numerous approach have been proposed. We review here most of them.