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Journal of Applied Mathematics
Volume 2013 (2013), Article ID 902972, 10 pages
http://dx.doi.org/10.1155/2013/902972
Research Article

A New Improved Parsimonious Multivariate Markov Chain Model

School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China

Received 12 November 2012; Revised 17 December 2012; Accepted 2 January 2013

Academic Editor: Marco H. Terra

Copyright © 2013 Chao Wang and Ting-Zhu Huang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

We present a new improved parsimonious multivariate Markov chain model. Moreover, we find a new convergence condition with a new variability to improve the prediction accuracy and minimize the scale of the convergence condition. Numerical experiments illustrate that the new improved parsimonious multivariate Markov chain model with the new convergence condition of the new variability performs better than the improved parsimonious multivariate Markov chain model in prediction.