A Bayesian Partition Model for Customer Attrition
Clive J. Hoggart, Jim E. Griffin · Kent Academic Repository (University of Kent) · 2001
This paper presents a nonlinear Bayesian model for covariates in a survival model with a surviving fraction. The work is a direct extension of the cure rate model of Chen et al. (1999). In their model the covariates depend naturally on the cure rate through a generalised linear model. We use a more flexible local model of the covariates utilizing the Bayesian partition model of Holmes et al. (1999). We apply the model to a large retail banking data set and compare our results with the generalised linear model used by Chen et al. (1999).