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.
Titolo: | Market segmentation via mixtures of constrained factor analyzers |
Autori interni: | |
Data di pubblicazione: | 2013 |
Handle: | http://hdl.handle.net/20.500.11769/76560 |
ISBN: | 9788834325568 |
Appare nelle tipologie: | 2.1 Contributo in volume (Capitolo o Saggio) |
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