Multivariate Outlier Identification Based on Robust Estimators of Location and Scatter
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Publisher
Springer Berlin Heidelberg
Link
http://link.springer.com/content/pdf/10.1007/978-3-642-35494-6_7
Reference29 articles.
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3. Becker, C., & Gather, U. (2001). The largest nonidentifiable outlier: a comparison of multivariate simultaneous outlier identification rules. Computational Statistics & Data Analysis, 36, 119–127.
4. Becker, C., & Paris Scholz, S. (2006). Deepest points and least deep points: robustness and outliers with MZE. In M. Spiliopoulou, R. Kruse, C. Borgelt, A. Nürnberger, & W. Gaul (Eds.), From data and information analysis to knowledge engineering (pp. 254–261). Heidelberg: Springer.
5. Bennett, M., & Willemain, T. (2001). Resistant estimation of multivariate location using minimum spanning trees. Journal of Statistical Computation and Simulation, 69, 19–40.
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1. Efficiency of the pMST and RDELA location and scatter estimators;AStA Advances in Statistical Analysis;2014-04-03
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