Bayesian nonparametric inference for discovery probabilities: credible intervals and large sample asymptotics

DOI10.5705/ss.202015.0250zbMath1362.62064arXiv1506.04915OpenAlexW1481277672MaRDI QIDQ2977533

Julyan Arbel, Bernardo Nipoti, Stefano Favaro, Yee Whye Teh

Publication date: 18 April 2017

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1506.04915

zbMATH Keywords

asymptoticsBayesian nonparametricssmoothing techniquecredible intervalsGibbs-type priorsdiscovery probabilityGood-Turing estimatortwo-parameter Poisson-Dirichletnormalized generalized Gamma prior

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)

Related Items (4)

Clustering dynamics in a class of normalised generalised gamma dependent priors ⋮ Sufficientness postulates for Gibbs-type priors and hierarchical generalizations ⋮ Approximating predictive probabilities of Gibbs-type priors ⋮ A simple proof of Pitman-Yor's Chinese restaurant process from its stick-breaking representation

This page was built for publication: Bayesian nonparametric inference for discovery probabilities: credible intervals and large sample asymptotics