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 th observation a species already observed with any given frequency in an enlarged sample of size , conditionally on a basic sample of size . Unfortunately the general result under Gibbs priors (Theorem 2), and consequently the explicit result under 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.
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