Dipartimento di Scienze Statistiche

PhD program in Statistics DSS Statistics Seminar April 24, 2026, 12:00 In person.Room V (CU002) Webinar^.https://uniroma1.zoom.us/j/83625004899?pwd=bXCtz0 mp759PUh2lkqT0BUoVa0Uegg.1 Passcode: 123456 Distances on random measures for Bayesian nonparametrics Marta Catalano Luiss University Random measures are a key component of many nonparametric models in Bayesian Statistics. Their infinite-dimensionality guarantees remarkable flexibility and generality but makes the investigation of theoretical and inferential properties more demanding. In this talk we underline how several of these properties can be investigated through suitable distances between the laws of the random measures. Some crucial desiderata for such distances are metrization of weak convergence, numerical estimation through samples, and tractability of analytical bounds: we achieve them by relying on optimal transport and integral probability metrics. Applications of our findings include measuring dependence in Bayesian nonparametric models, defining merging rates of opinions, developing two-sample tests for measure-valued data, and quantifying the error in approximate posterior inference.