Prediction of Future Random Events with the Condensed Negative Binomial Distribution

Abstract The condensed negative binomial distribution (CNBD) has been proposed as a stochastic model that is more appropriate for consumer purchasing behavior than is the common negative binomial distribution. Since this model was motivated previously and shown to fit single-period purchasing data, the focus here turns to the dynamics of the process, as reflected in the aggregate characteristics of interpurchase times and period-to-period predictions. The theoretical results are useful for comparing the predictive effectiveness of the CNBD with the commonly used negative binomial distribution.