Modal Principal Component Analysis

Principal component analysis (PCA) is a widely used method for data processing, such as for dimension reduction and visualization. Standard PCA is known to be sensitive to outliers, and thus, various robust PCA methods have been proposed. It has been shown that the robustness of many statistical met...

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Veröffentlicht in:	arXiv.org 2020-08
Hauptverfasser:	Sando, Keishi, Hino, Hideitsu
Format:	Artikel
Sprache:	eng
Schlagworte:	Data analysis Data points Data processing Influence functions Lower bounds Methods Outliers (statistics) Principal components analysis Robustness Statistical analysis Statistical methods
Online-Zugang:	Volltext
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