A Noninformative Bayesian Approach to Interval Estimation in Finite Population Sampling
提出一种无信息贝叶斯方法，利用Polya分布作为伪后验分布对有限总体中未观测成员进行区间估计，在标准方法难以应用时（如两中位数比值）仍有效，且点估计优于经典方法。
Abstract A noninformative Bayesian approach to interval estimation in finite population sampling is discussed. Given the sample, this method introduces the Polya distribution as a pseudo posterior distribution over the unobserved members of the population. In many cases this distribution yields interval estimates similar to those of standard frequentist theory. In addition, it can be used in situations where the standard methods are difficult to apply, for example, in producing an interval estimate for the ratio of two medians. We also consider related point estimation problems and observe that estimators derived from the pseudo posterior often perform better than classical alternatives.