M/G/1-型马尔可夫链的级增量截断逼近的级次几何收敛性

Q4 Decision Sciences
Katsuhisa Ouchi, H. Masuyama
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引用次数: 2

摘要

研究M/G/1型马尔可夫链的水平递增截断近似。LI截断近似有助于实现M/G/1范式,M/G/1范式是计算M/G/1型马尔可夫链平稳分布的框架。本文的主要结果是原始平稳分布与其LI截断近似之间的总变异距离的一个亚几何收敛公式。设均衡水平增量分布为次指数分布,向下转移矩阵为第一级。然后,我们证明了LI截断近似的总变异误差的收敛速度等于平衡水平增量分布尾部的收敛速度和原始平稳分布尾部的收敛速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
LEVEL-WISE SUBGEOMETRIC CONVERGENCE OF THE LEVEL-INCREMENT TRUNCATION APPROXIMATION OF M/G/1-TYPE MARKOV CHAINS
This paper considers the level-increment (LI) truncation approximation of M/G/1-type Markov chains. The LI truncation approximation is useful for implementing the M/G/1 paradigm, which is the framework for computing the stationary distribution of M/G/1-type Markov chains. The main result of this paper is a subgeometric convergence formula for the total variation distance between the original stationary distribution and its LI truncation approximation. Suppose that the equilibrium level-increment distribution is subexponential, and that the downward transition matrix is rank one. We then show that the convergence rate of the total variation error of the LI truncation approximation is equal to that of the tail of the equilibrium level-increment distribution and that of the tail of the original stationary distribution.
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来源期刊
Journal of the Operations Research Society of Japan
Journal of the Operations Research Society of Japan 管理科学-运筹学与管理科学
CiteScore
0.70
自引率
0.00%
发文量
12
审稿时长
12 months
期刊介绍: The journal publishes original work and quality reviews in the field of operations research and management science to OR practitioners and researchers in two substantive categories: operations research methods; applications and practices of operations research in industry, public sector, and all areas of science and engineering.
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