Central axes and peripheral points in high dimensional directional datasets

Annabella Astorino (), Manlio Gaudioso () and Alberto Seeger ()
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Annabella Astorino: Università delle Calabria
Manlio Gaudioso: Università delle Calabria
Alberto Seeger: University of Avignon

Computational Optimization and Applications, 2016, vol. 65, issue 2, No 2, 313-338

Abstract: Abstract We introduce a new notion of central axis for a finite set $$\{a_1,\ldots ,a_m\}$$ { a 1 , … , a m } of vectors in $$\mathbb {R}^n$$ R n . In tandem, we discuss different ways of measuring the dispersion of the data points $$a_i$$ a i ’s around the central axis. Finally, we explain how to detect numerically the most peripheral points of the given dataset.

Keywords: Central axis of a dataset; Conic barycenter; Conic circumcenter; Peripheral point; Outliers detection; Convex optimization; 90C25; 90C26; 90C40 (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s10589-014-9724-2

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