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  • Search: subject:"Robust clusterwise regression"
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Anti-fraud 1 Concentrated noise 1 International trade 1 Orthogonal regression 1 Outlier detection 1 Robust clusterwise regression 1 TCLUST 1 Thinning 1 Trimming 1
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Cerioli, Andrea 1 Perrotta, Domenico 1
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Advances in Data Analysis and Classification 1
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Robust clustering around regression lines with high density regions
Cerioli, Andrea; Perrotta, Domenico - In: Advances in Data Analysis and Classification 8 (2014) 1, pp. 5-26
Robust methods are needed to fit regression lines when outliers are present. In a clustering framework, outliers can be extreme observations, high leverage points, but also data points which lie among the groups. Outliers are also of paramount importance in the analysis of international trade...
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