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For: Serfling R, Mazumder S. Computationally easy outlier detection via projection pursuit with finitely many directions. J Nonparametr Stat 2013. [DOI: 10.1080/10485252.2013.766335] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Number Cited by Other Article(s)
1
Navarro-Esteban P, Cuesta-Albertos JA. High-dimensional outlier detection using random projections. TEST-SPAIN 2021. [DOI: 10.1007/s11749-020-00750-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
2
On masking and swamping robustness of leading nonparametric outlier identifiers for multivariate data. J MULTIVARIATE ANAL 2018. [DOI: 10.1016/j.jmva.2018.02.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
3
Skewness-based projection pursuit: A computational approach. Comput Stat Data Anal 2018. [DOI: 10.1016/j.csda.2017.11.001] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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