Papers20100623105844 < AI_GEOSTATS

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*Title:* Analysis of Rainfall Data by Robust Spatial Statistics using S+ SPATIALSTATS

*Date:* 1 May 1998

<strong>Authors: </strong>Marc G. Genton & Reinhard Furrer

<strong>Link: </strong> [[%ATTACHURL%/Genton_2.pdf][Genton_2.pdf]]

*Abstract:*

This paper discusses the use of robust geostatistical methods on a data set of rainfall measurements in Switzerland. The variables are detrended via non-parametric estimation penalized with a smoothing parameter. The optimal trend is computed with a smoothing parameter based on cross-validation. Then, the variogram is estimated by a highly robust estimator of scale. The parametric variogram model is fitted by generalized least squares, thus taking account of the variance-covariance structure of the variogram estimates. Comparison of kriging with the initial measurements is completed and yields interesting results. All these computations are done with the software S+SPATIALSTATS, extended with new functions in S+ that are made available.

REFERENCE

Journal of Geographic Information and Decision Analysis, Vol. 2, No. 2, pp. 116-126, 1998

Keywords: Robustness; Trend; Variogram; Generalized least squares; Kriging.

Topic revision: r3 - 2010-08-13 - 20:21:19 - TheresiaFreska

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