Multivariate outlier detection in exploration geochemistry

被引:295
|
作者
Filzmoser, P
Garrett, RG
Reimann, C
机构
[1] Vienna Tech Univ, Inst Stat & Probabil Theory, A-1040 Vienna, Austria
[2] Geol Survey Canada, Nat Resources Canada, Ottawa, ON K1A 0E8, Canada
[3] Geol Survey Norway, N-7491 Trondheim, Norway
关键词
multivariate outliers; robust statistics; exploration geochemistry; background;
D O I
10.1016/j.cageo.2004.11.013
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
A new method for multivariate outlier detection able to distinguish between extreme values of a normal distribution and values originating front a different distribution (outliers) is presented. To facilitate visualising multivariate outliers spatially on a map, the multivariate outlier plot, is introduced. In this plot different symbols refer to a distance measure from the centre of the distribution, taking into account the shape of the distribution, and different colours are used to signify the magnitude of the values for each variable. The method is illustrated using a real geochemical data set from far-northern Europe. It is demonstrated that important processes such as the input of metals from contamination sources and the contribution of sea-salts via marine aerosols to the soil can be identified and separated. (c) 2004 Elsevier Ltd. All rights reserved.
引用
收藏
页码:579 / 587
页数:9
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