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Resistant orthogonal procrustes analysis
Authors:Peter Verboon  Willem J Heiser
Institution:(1) Department of Data Theory, FSW, Leiden University, Wassenaarseweg 52, 2300 RB Leiden, The Netherlands
Abstract:In this paper two alternative loss criteria for the least squares Procrustes problem are studied. These alternative criteria are based on the Huber function and on the more radical biweight function, which are designed to be resistant to outliers. Using iterative majorization it is shown how a convergent reweighted least squares algorithm can be developed. In asimulation study it turns out that the proposed methods perform well over a specific range of contamination. When a uniform dilation factor is included, mixed results are obtained. The methods also yield a set of weights that can be used for diagnostic purposes.
Keywords:Resistance  Procrustes analysis  Outliers  Iterative majorization  Reweighted least squares
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