CLASSIFICATION PROBLEMS OF SAMPLES OF FINITE MIXTURES OF COMPOSITIONS

A discriminant technique based on mixture models is presented to be ap plied 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 techniq ue is compared empirically with the efficiency of the standard discrim inant technique based on logcontrast. Simulated compositional data and a real dataset are used to carry out these comparisons.