To analyse telecommunications marketing data which are usually made of discrete and continuous observations we consider a general framework to jointly model continuous, count and categorical variables under a nonparametric prior, which is induced through rounding latent variables having an unknown density with respect to Lebesgue measure. The approach is applied to model the joint density of traffic data for a portion of customers of an European mobile phone operator.

A Bayesian nonparametric model for data on different scales of measure; an application to customer base management of telecommunications companies.

CANALE, ANTONIO;
2013

Abstract

To analyse telecommunications marketing data which are usually made of discrete and continuous observations we consider a general framework to jointly model continuous, count and categorical variables under a nonparametric prior, which is induced through rounding latent variables having an unknown density with respect to Lebesgue measure. The approach is applied to model the joint density of traffic data for a portion of customers of an European mobile phone operator.
2013
Advances in Latent Variables
Advances in Latent Variables - Methods, Models and Applications
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3222947
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