A new class of prior distributions for metric-based models in the analysis of fully and partially ranked data is developed. This class is attractive because it provides a meaningful way to encapsulate prior information about the parameters of the model. Three examples illustrate the ideas...

In this paper, we study the drivers of customer satisfaction for financial services. We discuss a full Bayesian analysis based on data collected from customers of a leading financial services company. Our approach allows us to explicitly accommodate missing data and enables quantitative...

This paper uses free-knot and fixed-knot regression splines in a Bayesian context to develop methods for the nonparametric estimation of functions subject to shape constraints in models with log-concave likelihood functions. The shape constraints we consider include monotonicity, convexity and...

This paper develops a new family of Bayesian semi-parametric models. A particular member of this family is used to model option prices with the aim of improving out-of-sample predictions. A detailed empirical analysis is made for European index call and put options to illustrate the ideas.