Weighted and robust archetypal analysis

Manuel J.A. Eugster and Friedrich Leisch

Computational Statistics & Data Analysis, 2011, vol. 55, issue 3, 1215-1225

Abstract: Archetypal analysis represents observations in a multivariate data set as convex combinations of a few extremal points lying on the boundary of the convex hull. Data points which vary from the majority have great influence on the solution; in fact one outlier can break down the archetype solution. The original algorithm is adapted to be a robust M-estimator and an iteratively reweighted least squares fitting algorithm is presented. As a required first step, the weighted archetypal problem is formulated and solved. The algorithm is demonstrated using an artificial example, a real world example and a detailed simulation study.

Keywords: Robust; archetypal; analysis; M-estimator; Breakdown; point; Iteratively; reweighted; least; squares (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (8)

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