On Gaussian Markov processes and Polya processes

IF 0.8 4区管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Letters Pub Date : 2024-01-01 DOI:10.1016/j.orl.2023.107062

Kerry Fendick , Ward Whitt

引用次数: 0

Abstract

In previous work we characterized Gaussian Markov processes with stationary increments and showed that they arise as asymptotic approximations for stochastic point processes with a random rate such as Polya processes, which can be useful to model over-dispersion and path-dependent behavior in service system arrival processes. Here we provide additional insight into these stochastic processes.

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论高斯马尔可夫过程和波利亚过程

在之前的工作中，我们对具有静止增量的高斯马尔可夫过程进行了描述，并证明它们是具有随机速率的随机点过程（如波利亚过程）的渐近近似，可用于模拟服务系统到达过程中的过度分散和路径依赖行为。在此，我们将对这些随机过程提出更多见解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Operations Research Letters 管理科学-运筹学与管理科学

CiteScore

2.10

自引率

9.10%

发文量

111

审稿时长

83 days

期刊介绍： Operations Research Letters is committed to the rapid review and fast publication of short articles on all aspects of operations research and analytics. Apart from a limitation to eight journal pages, quality, originality, relevance and clarity are the only criteria for selecting the papers to be published. ORL covers the broad field of optimization, stochastic models and game theory. Specific areas of interest include networks, routing, location, queueing, scheduling, inventory, reliability, and financial engineering. We wish to explore interfaces with other fields such as life sciences and health care, artificial intelligence and machine learning, energy distribution, and computational social sciences and humanities. Our traditional strength is in methodology, including theory, modelling, algorithms and computational studies. We also welcome novel applications and concise literature reviews.