Estimating the difference between two binomial proportions will be investigated, where Bayesian, frequentist and fiducial (BFF) methods will be considered. Three vague priors will be used, the Jeffreys prior, a divergence prior and the probability matching prior. A probability matching prior is a prior distribution under which the posterior probabilities of certain regions coincide with their coverage probabilities. Fiducial inference can be viewed as a procedure that obtains a measure on a parameter space while assuming less than what Bayesian inference does, i.e. no prior. Fisher introduced the idea of fiducial probability and fiducial inference. In some cases the fiducial distribution is equivalent to the Jeffreys posterior. The performance of the Jeffreys prior, divergence prior and the probability matching prior will be compared to a fiducial method and other classical methods of constructing confidence intervals for the difference between two independent binomial parameters. These intervals will be compared and evaluated by looking at their coverage rates and average interval lengths. The probability matching and divergence priors perform better than the Jeffreys prior.

翻译：估计两个二进制比例之间的差别将进行调查, 其中将考虑贝耶斯、常客和教育(BFF)方法。 将使用三个模糊的前置概念, 前杰弗里、 前差、 前差和前比概率。 前概率匹配是先前的分布, 其中某些区域的后差或概率与其覆盖范围的概率相吻合。 可将误判视为一种程序, 该程序在假设参数空间的测量值低于贝耶斯的推断值时, 即没有以前的情况。 Fisher 引入了概率和误判的概念。 在某些情况下, 前差分布相当于杰弗里后差。 前差和前差的性能将比前差性方法和其他典型方法进行比较, 用来为两个独立的二进制参数之间的差异构建信任间隔。 这些间隔将通过查看其覆盖率和平均间隔来进行比较和评价。 前差和前差的可能性比前差更好。