Implementation of Upper Multinomial Bound Using Clustering
针对有限总体中大部分元素为零、少数为正的情况，提出用聚类方法处理多项分布上界，使样本中最多可含25个错误时仍能计算该界，且紧度损失不大。
Abstract The multinomial bound is a nonparametric bound for a finite population total when most elements have a value of zero and the remaining elements have positive values, such as occur in accounting and in threshold problems in the physical and biological sciences. Up to now, computational difficulties have restricted use of the multinomial bound to cases where the sample contains eight or less errors. The use of clustered errors described in this paper extends use of the multinomial bound to cases where the sample contains up to 25 errors, with only moderate loss in tightness of the bound.