Events and Meetings of Italian Statistical Society, Advances in Latent Variables - Methods, Models and Applications

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Market segmentation via mixtures of constrained factor analyzers
Francesca Greselin, Salvatore Ingrassia

Last modified: 2013-07-04


In this paper we introduce a procedure for the parameter estimation of mixtures of factor analyzers, which maximizes the likelihood function in a constrained parameter space, to overcome the well-known issue of singularities and to reduce spurious maxima of the likelihood function. A Monte Carlo study of the performance of the algorithm is provided. Finally the proposed approach is employed to provide a market segmentation, to model a set of quantitative variables provided by a telecom company, and related to the amount of services used by customers.

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