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On Perturbation Bounds for the Joint Stationary Distribution of Multivariate Markov Chain Models

Published online by Cambridge University Press:  28 May 2015

Wen Li ,
Lin Jiang ,
Wai-Ki Ching  and
Lu-Bin Cui
Wen Li*
Affiliation:
School of Mathematical Sciences, South China Normal University, Guangzhou, 510631, P.R. China
Lin Jiang*
Affiliation:
School of Mathematical Sciences, South China Normal University, Guangzhou, 510631, P.R. China
Wai-Ki Ching*
Affiliation:
Advanced Modeling and Applied Computing Laboratory, Department of Mathematics, The University of Hong Kong, Pokfulam Road, Hong Kong
Lu-Bin Cui*
Affiliation:
School of Mathematical Sciences, South China Normal University, Guangzhou, 510631, P.R. China
*
Corresponding author. Email: [email protected]
Corresponding author. Email: [email protected]
Corresponding author. Email: [email protected]
Corresponding author. Email: [email protected]
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Abstract

Multivariate Markov chain models have previously been proposed in for studying dependent multiple categorical data sequences. For a given multivariate Markov chain model, an important problem is to study its joint stationary distribution. In this paper, we use two techniques to present some perturbation bounds for the joint stationary distribution vector of a multivariate Markov chain with s categorical sequences. Numerical examples demonstrate the stability of the model and the effectiveness of our perturbation bounds.

Keywords

65M1078A48Multivariate Markov chain modelsstationary distribution vectorcondition numberrelative bound
Type
Research Article
Information
East Asian Journal on Applied Mathematics , Volume 3 , Issue 1 , February 2013 , pp. 1 - 17
Copyright
Copyright © Global-Science Press 2013

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