Improved Eaton Bounds for Linear Combinations of Bounded Random Variables, with Statistical Applications
有界随机变量线性组合的改进Eaton界及统计应用
The problem of evaluating tail probabilities for linear combinations of independent, possibly nonidentically distributed, bounded random variables arises in various statistical contexts, mainly connected with nonparametric inference. A remarkable inequality on such tail probabilities has been established by Eaton. The significance of Eaton's inequality is substantiated by a recent result of Pinelis showing that the minimum B EP of Eaton's bound B E and a traditional…