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Classification problems of samples of finite mixtures of compositions |
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| Authors: | Carles Barceló , Vera Pawlowsky Eric Grunsky |
| Affiliation: | (1) Department d'Informàtica i Matemàtica Aplicada, Escola Politècnica Superior, Universitat de Girona, 17071 Girona, Spain;(2) Department de Matemàtica Aplicada III, E.T.S. d'Enginyers de Camins, Canals i Ports, Universitat Politècnica de Catalunya, 08034 Barcelona, Spain;(3) Geological Survey Branch, Ministry of Energy Mines & Petroleum Resources, 1810, Blanshard St., V8V 1X4 Victoria, B.C., Canada |
| Abstract: | A discriminant technique based on mixture models is presented to be applied when observations are a sample of a mixture of compositions with each component following an additive logistic normal distribution on the d-dimensional simplex. The efficiency of this discriminant technique is compared empirically with the efficiency of the standard discriminant technique based on logcontrast. Simulated compositional data and a real dataset are used to carry out these comparisons. |
| Keywords: | discriminant analysis compositional data mixture models |
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