collaborators

6 papers

stat.ME2026

Bayesian inference on beta diversity via feature allocation models with imperfect detection

Federica Stolf, Tommaso Rigon, David B. Dunson

Beta diversity quantifies variation in species composition across ecological communities and is fundamental for understanding biodiversity patterns across space and environmental g…

stat.ML2025

Optimal and computationally tractable lower bounds for logistic log-likelihoods

Niccolò Anceschi, Cristian Castiglione, Tommaso Rigon +2

The logit transform is arguably the most widely-employed link function beyond linear settings. This transformation routinely appears in regression models for binary data and provid…

stat.ME2025

Nonparametric predictive inference for discrete data via Metropolis-adjusted Dirichlet sequences

Davide Agnoletto, Tommaso Rigon, David B. Dunson

This article is motivated by challenges in conducting Bayesian inferences on unknown discrete distributions, with a particular focus on count data. To avoid the computational disad…

stat.ME2025

Bayesian analysis of product feature allocation models

Lorenzo Ghilotti, Federico Camerlenghi, Tommaso Rigon

Feature allocation models are an extension of Bayesian nonparametric clustering models, where individuals can share multiple features. We study a broad class of models whose probab…

stat.ME2025

Bayesian nonparametric modeling of multivariate count data with an unknown number of traits

Lorenzo Ghilotti, Federico Camerlenghi, Tommaso Rigon +1

Feature and trait allocation models are fundamental objects in Bayesian nonparametrics and play a prominent role in several applications. Existing approaches, however, typically as…

stat.ME2025

A Bayesian theory for estimation of biodiversity

Tommaso Rigon, Ching-Lung Hsu, David B. Dunson

Statistical inference on biodiversity has a rich history going back to RA Fisher. An influential ecological theory suggests the existence of a fundamental biodiversity number, deno…