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Multivariate Markov chain models

  • Eric S. Fung
  • , Wai Ki Ching
  • , Sydney Chu
  • , Michael K. Ng*
  • , Wenan Zang
  • *Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

1 Citation (Scopus)

Abstract

In this paper we study tnultivariate Markov chain models for approximating a conventional Markov chain model with a huge number of states. We propose an efficient estimation method for the parameters in the proposed model. Numerical examples are given to illustrate the usefulness of the proposed model.

Original languageEnglish
Title of host publication2002 IEEE International Conference on Systems, Man and Cybernetics
EditorsAbdelkader El Kame1, Khaled Mellouli, Pierre Borne
PublisherIEEE
Pages295-299
Number of pages5
Volume7
ISBN (Print)0780374371
DOIs
Publication statusPublished - Oct 2002
Event2002 IEEE International Conference on Systems, Man and Cybernetics - Yasmine Hammamet, Tunisia
Duration: 6 Oct 20029 Oct 2002
https://ieeexplore.ieee.org/xpl/conhome/8325/proceeding (Conference Proceedings)

Publication series

NameProceedings of the IEEE International Conference on Systems, Man and Cybernetics
PublisherIEEE
ISSN (Print)1062-922X

Conference

Conference2002 IEEE International Conference on Systems, Man and Cybernetics
Country/TerritoryTunisia
CityYasmine Hammamet
Period6/10/029/10/02
Internet address

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

User-Defined Keywords

  • Markov chain
  • Estimation
  • Multivariate data

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