Bayesian Nonparametric Estimation of the Probability of Discovering New Species

Antonio Lijoi, Ramsés H. Mena and Igor Prünster

Biometrika, 2007, vol. 94, issue 4, 769-786

Abstract: We consider the problem of evaluating the probability of discovering a certain number of new species in a new sample of population units, conditional on the number of species recorded in a basic sample. We use a Bayesian nonparametric approach. The different species proportions are assumed to be random and the observations from the population exchangeable. We provide a Bayesian estimator, under quadratic loss, for the probability of discovering new species which can be compared with well-known frequentist estimators. The results we obtain are illustrated through a numerical example and an application to a genomic dataset concerning the discovery of new genes by sequencing additional single-read sequences of cdna fragments. Copyright 2007, Oxford University Press.

Date: 2007
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