The popularity of Bayesian nonparametric (BNP) inference is rapidly growing within both the academic community and practitioners. Indeed the BNP viewpoint naturally allows for rich and flexible probabilistic modeling and, via conditional (or posterior) distributions, for accurate function estimation, most notably of probability distributions, regression functions and hazard rates. After de Finetti ...