Asymptotic Properties of Bayesian Single Sampling Plans

Abstract

The model to be considered is based on a differentiable prior distribution, a general loss function, an operating characteristic written as an Edgeworth expansion, and sampling costs expressible as a polynomial in the sample size. Asymptotic expressions for the Bayesian single-sampling plan are derived and it is shown how previously known results may be found as special cases of the present one. The efficiency of non-optimum plans is discussed.