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 language | English |
|---|---|
| Title of host publication | 2002 IEEE International Conference on Systems, Man and Cybernetics |
| Editors | Abdelkader El Kame1, Khaled Mellouli, Pierre Borne |
| Publisher | IEEE |
| Pages | 295-299 |
| Number of pages | 5 |
| Volume | 7 |
| ISBN (Print) | 0780374371 |
| DOIs | |
| Publication status | Published - Oct 2002 |
| Event | 2002 IEEE International Conference on Systems, Man and Cybernetics - Yasmine Hammamet, Tunisia Duration: 6 Oct 2002 → 9 Oct 2002 https://ieeexplore.ieee.org/xpl/conhome/8325/proceeding (Conference Proceedings) |
Publication series
| Name | Proceedings of the IEEE International Conference on Systems, Man and Cybernetics |
|---|---|
| Publisher | IEEE |
| ISSN (Print) | 1062-922X |
Conference
| Conference | 2002 IEEE International Conference on Systems, Man and Cybernetics |
|---|---|
| Country/Territory | Tunisia |
| City | Yasmine Hammamet |
| Period | 6/10/02 → 9/10/02 |
| Internet address |
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UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
User-Defined Keywords
- Markov chain
- Estimation
- Multivariate data
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