Markov chains with transition delta-matrix: ergodicity conditions, invariant probability measures and applications

Author:

Abolnikov Lev1,Dukhovny Alexander2

Affiliation:

1. Loyola Marymount University, Department of Mathematics, Los Angeles 90045, CA, USA

2. San Francisco State University, Department of Mathematics, San Francisco 94132, CA, USA

Abstract

A large class of Markov chains with so-called Δm,n-and Δm,n-transition matrices (“delta-matrices”) which frequently occur in applications (queues, inventories, dams) is analyzed.The authors find some structural properties of both types of Markov chains and develop a simple test for their irreducibility and aperiodicity. Necessary and sufficient conditions for the ergodicity of both chains are found in the article in two equivalent versions. According to one of them, these conditions are expressed in terms of certain restrictions imposed on the generating functions Ai(z) of the elements of the ith row of the transition matrix, i=0,1,2,; in the other version they are connected with the characterization of the roots of a certain associated function in the unit disc of the complex plane. The invariant probability measures of Markov chains of both kinds are found in terms of generating functions. It is shown that the general method in some important special cases can be simplified and yields convenient and, sometimes, explicit results.As examples, several queueing and inventory (dam) models, each of independent interest, are analyzed with the help of the general methods developed in the article.

Publisher

Hindawi Limited

Subject

Applied Mathematics,Modelling and Simulation,Statistics and Probability

Cited by 46 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3