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Influence and sensitivity measures in correspondence analysis
Authors:Avner Bar-Hen  Frédéric Mortier
Institution:1. Faculté de Saint Jér?me, IMEP, Laboratoire de biomathématiques case 462 , Université Aix-Marseille III , 13397, Marseille Cedex 20, France;2. Laboratoire de Statistique et Probabilités, Bat. M2 , Université des Sciences et Technologies de Lille , 59655, Villeneuve d’Ascq Cedex, France avner@bar-hen.net;4. Laboratoire de Statistique et Probabilités, Bat. M2 , Université des Sciences et Technologies de Lille , 59655, Villeneuve d’Ascq Cedex, France
Abstract:Since correspondence analysis appears to be sensitive to outliers, it is important to be able to evaluate the sensitivity of the data on the results. This article deals with measuring the influence of rows and columns on the results obtained with correspondence analysis. To establish the influence of individuals on the analysis, we use the notion of influence curve and we propose a general criterion based on the mean square error to measure the sensitivity of the correspondence analysis and its robustness. A numerical example is presented to illustrate the notions developed in this article.
Keywords:Correspondence analysis  Influence curve  Mean square error
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