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stat.ME2026
Bayesian discovery of species in multiple areas
Alessandro Colombi, Raffaele Argiento, Federico Camerlenghi +1
In ecology, the description of species composition and biodiversity calls for statistical methods that involve estimating features of interest in unobserved samples based on an obs…
stat.ME2026
Confidence intervals for maximum unseen probabilities, with application to sequential sampling design
Alessandro Colombi, Mario Beraha, Amichai Painsky +1
Discovery problems often require deciding whether additional sampling is needed to detect all categories whose prevalence exceeds a prespecified threshold. We study this question u…
stat.ME2024
Hierarchical Mixture of Finite Mixtures
Alessandro Colombi, Raffaele Argiento, Federico Camerlenghi +1
Statistical modelling in the presence of data organized in groups is a crucial task in Bayesian statistics. The present paper conceives a mixture model based on a novel family of B…