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引用次数: 0
摘要
在本文中,我们得到了延迟更新函数的一些 "一般 "双面边界,即这些边界对任意的到达时间分布都有效。此外,我们还给出了一连串单调非递减(非递增)的下(上)限,这些下(上)限收敛于延迟更新函数。通过考虑到达时间分布的几个老化或可靠性等级(如、\(DFR\),有界平均残余寿命,\(NBUE\),\(NWUE\),有界故障率,\(DMRL\),\(IMRL\)),我们给出了延迟更新函数的上界和下界,此外,通过假设第一个到达时间和随后的到达时间之间的通常随机顺序,我们给出了收敛到延迟更新函数的单调非递减(非递增)下(上)界序列。此外,我们还给出了延迟更新函数与普通更新函数的一些边界序列。还给出了延迟更新密度的单调非递减(非递增)下(上)界序列。最后,我们得到了有限区间内预期更新次数的上界和下界,从而改进了 Lorden (Ann Math Statist 41:520-527, 1970) 和 Losidis and Politis (2022) 所得到的普通更新过程下有限区间内预期更新次数的上界。
Two-sided Bounds for some Quantities in the Delayed Renewal Process
In this paper we obtain some “general” two-sided bounds for the delayed renewal function, in the sense that the bounds are valid for any arbitrary distributions of the inter-arrival times. Also, we give a sequence of monotone non-decreasing (non-increasing) lower (upper) general bounds converging to the delayed renewal function. By considering several aging or reliability classes for the distribution of the interarrival times (e.g., \(DFR\), bounded mean residual lifetime, \(NBUE\), \(NWUE\), bounded failure rate, \(DMRL\), \(IMRL\)) we give upper and lower bounds for the delayed renewal function, and moreover by assuming the usual stochastic order between the first and the subsequent interarrival times, we give sequences of monotone non-decreasing (non-increasing) lower (upper) bounds converging to the delayed renewal function. Also, some sequences of bounds for the delayed renewal function in terms of the ordinary renewal function are given. Sequences of monotone non-decreasing (non-increasing) lower (upper) bounds for the delayed renewal density are also given. Finally, we obtain upper and lower bounds for the expected number of renewals over a finite interval, and as a result, we get an improvement of the upper bounds obtained by Lorden (Ann Math Statist 41:520–527, 1970) and Losidis and Politis (2022) for the expected number of renewals over a finite interval under the ordinary renewal process.
期刊介绍:
Methodology and Computing in Applied Probability will publish high quality research and review articles in the areas of applied probability that emphasize methodology and computing. Of special interest are articles in important areas of applications that include detailed case studies. Applied probability is a broad research area that is of interest to many scientists in diverse disciplines including: anthropology, biology, communication theory, economics, epidemiology, finance, linguistics, meteorology, operations research, psychology, quality control, reliability theory, sociology and statistics.
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