大强度区域中具有随机延迟簇到达和相关噪声的散粒噪声过程

IF 0.9 4区 数学 Q3 STATISTICS & PROBABILITY
Bo Li, G. Pang
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引用次数: 1

摘要

摘要我们研究了具有聚类到达的散粒噪声过程,其中每个聚类中的实体可能经历随机延迟(可能是相关的),并且每个聚类内的噪声可能是相关联的。我们证明了该过程在大强度渐近状态下的函数极限定理,其中到达率变大,而散粒形状函数、簇大小、延迟和噪声是不可缩放的。在函数中心极限定理中,极限过程是连续的高斯过程(假设到达过程满足具有布朗运动极限的函数中心极限理论)。我们使用依赖结构的几个例子来讨论随机延迟之间的依赖性和每个簇内的噪声之间的依赖关系的影响。我们还研究了具有集群/批到达的无限服务器队列,其中每个批中的客户在接收服务之前可能会经历随机延迟,具有类似的依赖结构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Shot noise processes with randomly delayed cluster arrivals and dependent noises in the large-intensity regime
Abstract We study shot noise processes with cluster arrivals, in which entities in each cluster may experience random delays (possibly correlated), and noises within each cluster may be correlated. We prove functional limit theorems for the process in the large-intensity asymptotic regime, where the arrival rate gets large while the shot shape function, cluster sizes, delays, and noises are unscaled. In the functional central limit theorem, the limit process is a continuous Gaussian process (assuming the arrival process satisfies a functional central limit theorem with a Brownian motion limit). We discuss the impact of the dependence among the random delays and among the noises within each cluster using several examples of dependent structures. We also study infinite-server queues with cluster/batch arrivals where customers in each batch may experience random delays before receiving service, with similar dependence structures.
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来源期刊
Advances in Applied Probability
Advances in Applied Probability 数学-统计学与概率论
CiteScore
2.00
自引率
0.00%
发文量
64
审稿时长
6-12 weeks
期刊介绍: The Advances in Applied Probability has been published by the Applied Probability Trust for over four decades, and is a companion publication to the Journal of Applied Probability. It contains mathematical and scientific papers of interest to applied probabilists, with emphasis on applications in a broad spectrum of disciplines, including the biosciences, operations research, telecommunications, computer science, engineering, epidemiology, financial mathematics, the physical and social sciences, and any field where stochastic modeling is used. A submission to Applied Probability represents a submission that may, at the Editor-in-Chief’s discretion, appear in either the Journal of Applied Probability or the Advances in Applied Probability. Typically, shorter papers appear in the Journal, with longer contributions appearing in the Advances.
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