Multivariate outlier detection in exploration geochemistry

Authors:
Peter Filzmoser;Robert G. Garrett;Clemens Reimann
Affiliations:
Institute of Statistics and Probability Theory, Vienna University of Technology, Wiedner Hauptstr. 8-10, A-1040 Wien, Austria;Geological Survey of Canada, Natural Resources Canada, 601 Booth Street, Ottawa, Ontario, Canada, K1A 0E8;Geological Survey of Norway, N-7491 Trondheim, Norway
Venue:
Computers & Geosciences
Year:
2005

Citing 2
Cited 6

A fast algorithm for the minimum covariance determinant estimator

Technometrics
A robust and efficient adaptive reweighted estimator of multivariate location and scatter

Journal of Multivariate Analysis

Outlier identification in high dimensions

Computational Statistics & Data Analysis
Estimation of water surface elevations for the Everglades, Florida

Computers & Geosciences
Detection of multivariate outliers in business survey data with incomplete information

Advances in Data Analysis and Classification
Delimiting imprecise regions with georeferenced photos and land coverage data

W2GIS'11 Proceedings of the 10th international conference on Web and wireless geographical information systems
Interpretation of multivariate outliers for compositional data

Computers & Geosciences
WCOID-DG: An approach for case base maintenance based on Weighting, Clustering, Outliers, Internal Detection and Dbsan-Gmeans

Journal of Computer and System Sciences

Quantified Score

Hi-index	0.00

Visualization

Abstract

A new method for multivariate outlier detection able to distinguish between extreme values of a normal distribution and values originating from 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.