{"title":"Two-sided Bounds for some Quantities in the Delayed Renewal Process","authors":"Stathis Chadjiconstantinidis","doi":"10.1007/s11009-024-10088-9","DOIUrl":null,"url":null,"abstract":"<p>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., <span>\\(DFR\\)</span>, bounded mean residual lifetime, <span>\\(NBUE\\)</span>, <span>\\(NWUE\\)</span>, bounded failure rate, <span>\\(DMRL\\)</span>, <span>\\(IMRL\\)</span>) 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.</p>","PeriodicalId":18442,"journal":{"name":"Methodology and Computing in Applied Probability","volume":"70 1","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Methodology and Computing in Applied Probability","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s11009-024-10088-9","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0
Abstract
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.
The following alphabetical listing of topics of interest to the journal is not intended to be exclusive but to demonstrate the editorial policy of attracting papers which represent a broad range of interests:
-Algorithms-
Approximations-
Asymptotic Approximations & Expansions-
Combinatorial & Geometric Probability-
Communication Networks-
Extreme Value Theory-
Finance-
Image Analysis-
Inequalities-
Information Theory-
Mathematical Physics-
Molecular Biology-
Monte Carlo Methods-
Order Statistics-
Queuing Theory-
Reliability Theory-
Stochastic Processes