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

This paper discusses the use of robust geostatistical methods on a data set of rainfall measurements for Switzerland. The variables are detrended via nonparametric estimation penalized with a smoothing parameter. The optimal trend is computed with a smoothing parameter based on cross-validation. The variogram is then 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 yields interesting results. All these computations are done with the software S+SPATIALSTATS, extended with new functions in S+ that are made available.