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Kriging for large data sets: A tentative comprehensive review

Abstract : 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.
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Contributor : Thomas Romary Connect in order to contact the contributor
Submitted on : Wednesday, April 6, 2011 - 10:33:30 AM
Last modification on : Wednesday, November 17, 2021 - 12:31:19 PM


  • HAL Id : hal-00583630, version 1


Thomas Romary. Kriging for large data sets: A tentative comprehensive review. 2009. ⟨hal-00583630⟩



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