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stat.ME2026
Bayesian nonparametric inference for modal missing species and features
Alessandro Colombi, Mario Beraha, Daniele Durante +1
Species and feature sampling problems arise naturally whenever each observed unit is associated with one or more labels from a countable alphabet, and inference focuses on the unob…
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…