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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…
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…
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…
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…
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…
Bayesian nonparametric modeling of latent partitions via Stirling-gamma priors
Alessandro Zito, Tommaso Rigon, David B. Dunson
Dirichlet process mixtures are particularly sensitive to the value of the precision parameter controlling the behavior of the latent partition. Randomization of the precision throu…