CSP 2017 Online Program

Probability Density for Repeated Events (303349)

Keywords: Repeated events, survival, hazards, logistic regression, customer relationship management

In customer relationship management (CRM) or consumer finance it is important to predict the time of repeated events. These repeated events might be a purchase, service visit, or late payment. Specifically, the goal is to find the probability density for the time to first event, the probability density for the time to second event, etc. Two approaches are presented and contrasted. One approach uses discrete time hazard modeling (DTHM). The second, a distinctly different approach, uses multinomial logistic model (MLM). Both DTHM and MLM satisfy an important consistency criterion which is to provide probability densities whose average across all customers equals the empirical population average. DTHM requires fewer models if the number of repeated events is small. MLM requires fewer models if the time horizon is small. SAS® code is provided through a simulation in order to illustrate the two approaches.