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A0191
Title: Functional principal components for concentration curves Authors:  Enea Bongiorno - Universita del Piemonte Orientale (Italy) [presenting]
Aldo Goia - University of Eastern Piedmont Amedeo Avogadro (Italy)
Abstract: Concentration curves are widely used in economic studies (inequality, poverty, differentiation, etc.). From a model point of view, such curves can be seen as constrained functional data that refer to the objects oriented data analysis literature. In fact, the family of concentration curves lacks of very basilar structures like the vectorial one and, hence, should be treated with ad hoc methods. The aim is to take care of such lacks providing a rigorous functional framework for concentration curves where it is possible to define Functional Principal Component Analysis (FPCA). The latter technique is then implemented and used to explore functional dataset.