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A Wavelet-Based Computational Framework for a Block-Structured Markov Chain with a Continuous Phase Variable

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成果类型:
期刊论文
作者:
Jiang, Shuxia;Liu, Nian;Liu, Yuanyuan
通讯作者:
Yuanyuan Liu
作者机构:
[Jiang, Shuxia] Cent South Univ Forestry & Technol, Sch Traff & Logist, Changsha 410004, Peoples R China.
[Liu, Nian] Michigan State Univ, Dept Stat & Probabil, E Lansing, MI 48824 USA.
[Liu, Yuanyuan] Cent South Univ, Sch Math & Stat, HNP LAMA, New Campus, Changsha 410083, Peoples R China.
通讯机构:
[Yuanyuan Liu] S
School of Mathematics and Statistics, HNP-LAMA, New Campus, Central South University, Changsha 410083, China<&wdkj&>Author to whom correspondence should be addressed.
语种:
英文
关键词:
Markov chains;stationary distribution;wavelet transform;numerical algorithm
期刊:
Mathematics
ISSN:
2227-7390
年:
2023
卷:
11
期:
7
页码:
1587-
基金类别:
Methodology, Y.L.; Software, S.J.; Writing—original draft, S.J., Y.L. and N.L.; Writing—review and editing, Y.L and N.L.; Visualization, S.J. and N.L.; Funding acquisition, Y.L. All authors have read and agreed to the published version of the manuscript. This research was funded in part by the National Natural Science Foundation of China (Grants No. 11971486).
机构署名:
本校为第一机构
院系归属:
交通运输与物流学院
摘要:
We consider the computing issues of the steady probabilities for block-structured discrete-time Markov chains that are of upper-Hessenberg or lower-Hessenberg transition kernels with a continuous phase set. An effective computational framework is proposed based on the wavelet transform, which extends and modifies the arguments in the literature for quasi-birth-death (QBD) processes. A numerical procedure is developed for computing the steady probabilities based on the fast discrete wavelet transform, and sev...

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