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Robust Spatial Data Analysis of Lake Geneva Sediments with S+SpatialStats


Furrer, R (1999). Robust Spatial Data Analysis of Lake Geneva Sediments with S+SpatialStats. Systems Research and Information Science, 8(4):257-272.

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.

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.

Statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Mathematics
Dewey Decimal Classification:510 Mathematics
Uncontrolled Keywords:Robustness; Trend; Variogram; Generalized least squares; Kriging
Language:English
Date:1999
Deposited On:29 Nov 2010 16:27
Last Modified:05 Apr 2016 13:26
Publisher:UNSPECIFIED
ISSN:0882-3014
Related URLs:http://infoscience.epfl.ch/record/83766

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