In many applications, data exhibit skewness and in this paper we present a new family of density functions modeling skewness based on a transformation, analagous to those of location and scale. Here we note that location will always refer to mode. Hence, in order to model data to include shape,...

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 develops a new family of Bayesian semiparametric 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

Management decisions regarding maintenance protocols critically hinge on the underlying probability distribution of the time between failures in most repairable systems. Replacement of the system with a new one resets the system age to zero, whereas a repair does not alter the system age but may...

This paper develops an estimation strategy for and then applies a spatial autoregressive multinomial probit model to account for both spatial clustering and cross-alternative correlation. Estimation is achieved using Bayesian techniques with Gibbs and the generalized direct sampling (GDS). The...

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...