Bayesian Sequential Tests for Comparing the Number of Species in Two Populations

Abstract

We study a problem of scquentially comparing the number of species in two populations. We consider a sequential Bayesian approach which incorporates a sampling cost and a misclassification loss, and examine optimal and sub-optimal stopping rules. The optimal stopping rule is shown to be truncated when the prior distribution of the number of species is bounded. or when the prior is unbounded and satisfies certain conditions.