Bayesian inference on the exponentiated Kumaraswamy distribution with applications

Abstract

We discuss Bayesian estimation of the exponentiated Kumaraswamy distribution, based on a location-scale-shape parameterisation. The parameterisation facilitates prior elicitation and interpretation of results, but potentially entails identifiability issues that are addressed through a hierarchical weakly informative prior setting. Our HMC implementation enables off-the-shelf utility for practitioners, and is illustrated on synthetic and real data.

11 pages 9 figures