English

A note on a Bayesian nonparametric estimator of the discovery probability

Statistics Theory 2013-04-04 v1 Statistics Theory

Abstract

Favaro, Lijoi, and Pruenster (2012, Biometrics, 68, 1188--1196) derive a novel Bayesian nonparametric estimator of the probability of detecting at the (n+m+1)(n+m+1)th observation a species already observed with any given frequency in an enlarged sample of size n+mn+m, conditionally on a basic sample of size nn. Unfortunately the general result under Gibbs priors (Theorem 2), and consequently the explicit result under (α,θ)(\alpha, \theta) Poisson-Dirichlet priors (Proposition 3), appear to be wrong. Here we provide the correct formulas for both the results, obtained by means of a new technique devised in Cerquetti (2013). We verify the correctness of our derivation by an explicit counterproof for the two-parameter Poisson-Dirichlet case.

Keywords

Cite

@article{arxiv.1304.1030,
  title  = {A note on a Bayesian nonparametric estimator of the discovery probability},
  author = {Annalisa Cerquetti},
  journal= {arXiv preprint arXiv:1304.1030},
  year   = {2013}
}

Comments

9 pages

R2 v1 2026-06-21T23:53:13.575Z