Approximately Bayesian Inference
针对标量参数的统计推断，提出一种度量区间估计系统与贝叶斯形式接近程度的方法，并分析多种非贝叶斯区间估计方法。
Abstract Consider statistical inference about a scalar parameter and suppose that information about that parameter is to be summarized by a system of interval estimates. It is well known that methods of interval estimation that do not correspond to Bayesian inference with respect to some prior distribution have some logical difficulties. This article proposes a measure of how close a system of interval estimates is to being of Bayesian form. Using this measure, several non-Bayesian methods of interval estimation are analyzed; these results are illustrated on several examples.