A Bayesian nonparametric model for data on different scales of measure; an application to customer base management of telecommunications companies.
Antonio Carlos Canale, David Banjerdpongchai · Padua Research Archive (University of Padova) · 2013
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.