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Statistical Identification of Markov Chain on Trees
Joint Authors
Xiang, Xuyan
Zhang, Xiao
Mo, Xiaoyun
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-03-28
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
The theoretical study of continuous-time homogeneous Markov chains is usually based on a natural assumption of a known transition rate matrix (TRM).
However, the TRM of a Markov chain in realistic systems might be unknown and might even need to be identified by partially observable data.
Thus, an issue on how to identify the TRM of the underlying Markov chain by partially observable information is derived from the great significance in applications.
That is what we call the statistical identification of Markov chain.
The Markov chain inversion approach has been derived for basic Markov chains by partial observation at few states.
In the current letter, a more extensive class of Markov chain on trees is investigated.
Firstly, a type of a more operable derivative constraint is developed.
Then, it is shown that all Markov chains on trees can be identified only by such derivative constraints of univariate distributions of sojourn time and/or hitting time at a few states.
A numerical example is included to demonstrate the correctness of the proposed algorithms.
American Psychological Association (APA)
Xiang, Xuyan& Zhang, Xiao& Mo, Xiaoyun. 2018. Statistical Identification of Markov Chain on Trees. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1205998
Modern Language Association (MLA)
Xiang, Xuyan…[et al.]. Statistical Identification of Markov Chain on Trees. Mathematical Problems in Engineering No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1205998
American Medical Association (AMA)
Xiang, Xuyan& Zhang, Xiao& Mo, Xiaoyun. Statistical Identification of Markov Chain on Trees. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1205998
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1205998