Continuity for Kriging with Moving Neighborhood
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By definition, kriging with a moving neighborhood consists in kriging each target point from a subset of data that varies with the target. When the target moves, data that were within the neighborhood are suddenly removed from the neighborhood. There is generally no screen effect, and the weight of such data goes suddenly from a non-zero value to a value of zero. This results in a discontinuity of the kriging map. Here a method to avoid such a discontinuity is proposed. It is based on the penalization of the outermost data points of the neighborhood, and amounts to considering that these points values are spoiled with a random error having a variance that increases infinitely when they are about to leave the neighborhood. Additional details are given regarding how the method is to be carried out, and properties are described. The method is illustrated by simple examples. While it appears to be similar to continuous kriging with a smoothing kernel, it is in fact based on a much simpler formalism.
KeywordsPenalized kriging Continuous kriging Kriging weights
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- Babak O, Deutsch CV (2008) Two new approaches to avoid large kriging weights to end samples in strings of data. In: Ortiz JM, Emery X (eds) Geostats2008, Proceedings of the 8th international geostatistics congress, FCFM—Gecamin, vol 1, pp 369–378 Google Scholar
- Babak O, Deutsch CV (2009) Successive kriging for estimation and simulation in a finite domain. SME Trans 326:10–15 Google Scholar
- Chilès J-P, Delfiner P (1999) Geostatistics, modeling spatial uncertainty. Wiley, New York Google Scholar
- Cressie N (1991) Statistics for spatial data. Wiley, New York (reprinted 1993) Google Scholar
- Furrer R, Genton MG, Nychka DW (2006) Covariance tapering for interpolation of large spatial data sets. J Comput Graph Stat 5(3):502–523 Google Scholar
- Wackernagel H (2003) Multivariate geostatistics: an introduction with applications, 3rd edn. Springer, Berlin Google Scholar