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Communications in Statistics - Theory and Methods Volume 34, 2005 - Issue 8
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Multivariate Analysis

A New Approach for Detecting Multivariate Outliers

Shaogen Gao Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China; Beijing Genomics Institute, Chinese Academy of Sciences, Beijing, ChinaCorrespondence[email protected]
,
Guoying Li Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China; Beijing Genomics Institute, Chinese Academy of Sciences, Beijing, China
&
Dongqian Wang School of Mathematical and Computing Sciences, Victoria University of Wellington, New Zealand
Pages 1857-1865 | Received 16 Apr 2004, Accepted 17 Feb 2005, Published online: 02 Sep 2006

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Xuqing Liu, Feng Gao, Yandong Wu & Zhiguo Zhao. (2018) Detecting outliers and influential points: an indirect classical Mahalanobis distance-based method. Journal of Statistical Computation and Simulation 88:11, pages 2013-2033.
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I. B. Mohamed, A. Rambli, N. Khaliddin & A. I. N. Ibrahim. (2016) A New Discordancy Test in Circular Data Using Spacings Theory. Communications in Statistics - Simulation and Computation 45:8, pages 2904-2916.
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Amanda F. Mejia, Mary Beth Nebel, Ani Eloyan, Brian Caffo & Martin A. Lindquist. (2017) PCA leverage: outlier detection for high-dimensional functional magnetic resonance imaging data. Biostatistics 18:3, pages 521-536.
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Timothy E. Smetek & Kenneth W. Bauer. (2007) Finding Hyperspectral Anomalies Using Multivariate Outlier Detection. Finding Hyperspectral Anomalies Using Multivariate Outlier Detection.

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