P.Filzmoser 137 The method FGR is implemented in R (http://cran.r-project.org)as a con- tributed package called mvoutlier.Special symbols for the value of the robust Maha- lanobis distance and colors for the coordinate values are suggested to visualize the struc- ture of the multivariate outliers(for details see Filzmoser et al.,2005). Acknowledgment I am grateful to Prof.Yuriy Kharin for the excellent cooperation and for all his work to organize this wonderful conference.Moreover,I wish to thank the referees for interesting and helpful comments. References V.Barnett and T.Lewis.Outliers in Statistical Data.Wiley Sons,New York,3rd edition,1994. C.Becker and U.Gather.The masking breakdown point of multivariate outlier identifi- cation rules.J.Am.Statist.Assoc.,94(447):947-955,1999 C.Becker and U.Gather.The largest nonidentifiable outlier:A comparison of multivari- ate simultaneous outlier identification rules.Computational Statistics Data Analysis, 36:119-127,2001. P.L.Davies.Asymptotic behavior of S-estimators of multivariate location and dispersion matrices.The Annals of Statistics,15:1269-1292,1987. H.Doleisch,M.Gasser,and H.Hauser.Interactive feature specification for focus+context visualization of complex simulation data.In Proc.of the Joint IEEE TCVG-EG Symp. onis.,pages239-248,2003 P.Filzmoser,R.G.Garrett,and C.Reimann.Multivariate outlier detection in exploration geochemistry.Computers and Geosciences,2005.In press. R.G.Garrett.The chi-square plot:A tool for multivariate outlier recognition.Journal of Geochemical Exploration,32:319-341,1989. A.Genz and F.Bretz.Numerical computation of multivariate t-probabilities with appli- cation to power calculation of multiple contrasts.Journal of Statistical Computation and Simulation,63:361-378,1999. D.Gervini.A robust and efficient adaptive reweighted estimator of multivariate location and scatter.Journal of Multivariate Analysis,84:116-144,2003. R.Gnanadesikan and J.R.Kettenring.Robust estimates,residuals,and outlier detection with multiresponse data.Biometrics,28:81-124,1972 J.T.Kent and D.E.Tyler.Constrained M-estimation for multivariate location and scatter. The Annals of Statistics,24(3):1346-1370,1996.P. Filzmoser 137 The method FGR is implemented in R (http://cran.r-project.org) as a con￾tributed package called mvoutlier. Special symbols for the value of the robust Maha￾lanobis distance and colors for the coordinate values are suggested to visualize the struc￾ture of the multivariate outliers (for details see Filzmoser et al., 2005). Acknowledgment I am grateful to Prof. Yuriy Kharin for the excellent cooperation and for all his work to organize this wonderful conference. Moreover, I wish to thank the referees for interesting and helpful comments. References V. Barnett and T. Lewis. Outliers in Statistical Data. Wiley & Sons, New York, 3rd edition, 1994. C. Becker and U. Gather. The masking breakdown point of multivariate outlier identifi- cation rules. J. Am. Statist. Assoc., 94(447):947–955, 1999. C. Becker and U. Gather. The largest nonidentifiable outlier: A comparison of multivari￾ate simultaneous outlier identification rules. Computational Statistics & Data Analysis, 36:119–127, 2001. P.L. Davies. Asymptotic behavior of S-estimators of multivariate location and dispersion matrices. The Annals of Statistics, 15:1269–1292, 1987. H. Doleisch, M. Gasser, and H. Hauser. Interactive feature specification for focus+context visualization of complex simulation data. In Proc. of the Joint IEEE TCVG – EG Symp. on Vis., pages 239–248, 2003. P. Filzmoser, R.G. Garrett, and C. Reimann. Multivariate outlier detection in exploration geochemistry. Computers and Geosciences, 2005. In press. R.G. Garrett. The chi-square plot: A tool for multivariate outlier recognition. Journal of Geochemical Exploration, 32:319–341, 1989. A. Genz and F. Bretz. Numerical computation of multivariate t-probabilities with appli￾cation to power calculation of multiple contrasts. Journal of Statistical Computation and Simulation, 63:361–378, 1999. D. Gervini. A robust and efficient adaptive reweighted estimator of multivariate location and scatter. Journal of Multivariate Analysis, 84:116–144, 2003. R. Gnanadesikan and J.R. Kettenring. Robust estimates, residuals, and outlier detection with multiresponse data. Biometrics, 28:81–124, 1972. J.T. Kent and D.E. Tyler. Constrained M-estimation for multivariate location and scatter. The Annals of Statistics, 24(3):1346–1370, 1996