Bayesian nonparametric mixture models represent a powerful statistical framework that extends traditional mixture modelling by allowing the number of mixture components to be inferred from the data ...

Bayesian methods for dynamic models in marketing have so far been parametric. For instance, it is invariably assumed that model errors emerge from normal distributions. Yet using arbitrary ...

This paper presents semiparametric identification results for the Rust (1994) class of discrete choice dynamic programming (DCDP) models. We develop sufficient conditions for identification of the ...