3 papers
math.ST2026
Bayesian Nonparametric Privacy-Preserving Synthetic Data Generation: I. Discrete Data
Maria Chiara Menicucci, Mario Beraha, Stefano Favaro +1
Synthetic data generation is a powerful approach to privacy-preserving statistical analysis, where data-release mechanisms are governed by a privacy-utility tradeoff: they should p…
stat.ME2026
Quasi-Bayes empirical Bayes estimation of sums of random variables
Stefano Favaro, Sandra Fortini
The estimation of sums of functions of observable and unobservable variables is a long-standing problem in statistics with applications across many domains. Empirical Bayes methods…
math.ST2026
Asymptotic regimes for maximum likelihood estimation in the Ewens--Pitman model: When the strength parameter matters
Filippo Ascolani, Mario Beraha, Stefano Favaro
We study the large sample asymptotic behaviour of the Maximum Likelihood Estimator of the discount and strength parameters in the Ewens--Pitman model for random partitions,…