论文标题
基于DFR和DFRA分布的GOSS的期望上限
On upper bounds on expectations of gOSs based on DFR and DFRA distributions
论文作者
论文摘要
我们关注的问题是建立基于属于分布家族的基础CDF的最佳上限，其平均分布率降低和失败率降低。 Bieniek先前已经考虑了这个问题[关于DFR和DFRA家族的广义订单统计数据的投影范围，统计数据，2006年； 40：339--351]，他通过使用统一的概括统计统计统计量的密度函数的投影建立了上部非负均值范围，并在正确选择的凸锥上建立了密度函数的组合物和指数分布函数。在本文中，我们可能通过改善Bieniek在某些特定情况下获得的零界限来获得负上限。我们以任意命令的中心绝对时刻产生的规模单位表示界限。我们还描述了可达到的条件。
We focus on the problem of establishing the optimal upper bounds on generalized order statistics which are based on the underlying cdf belonging to the family of distributions with decreasing failure rate and decreasing failure rate on the average. This issue has been previously considered by Bieniek [Projection bounds on expectations of generalized order statistics from DFR and DFRA families, Statistics, 2006; 40: 339--351], who established upper nonnegative mean-variance bounds with use of the projections of the compositions of density functions of the uniform generalized order statistic and the exponential distribution function onto the properly chosen convex cones. In this paper we obtain possibly negative upper bounds, by improving the zero bounds obtained by Bieniek for some particular cases of gOSs. We express the bounds in the scale units generated by the central absolute moments of arbitrary orders. We also describe the attainability conditions.
