DocumentCode
2852127
Title
A New Estimation Method for Multivariate Markov Chain Model with Application in Demand Predictions
Author
Zhu, Dong-Mei ; Ching, Wai-Ki
Author_Institution
Dept. of Math., Univ. of Hong Kong, Hong Kong, China
fYear
2010
fDate
13-15 Aug. 2010
Firstpage
126
Lastpage
130
Abstract
In this paper, we propose a new estimation method for the parameters of a multivariate Markov chain model. In the new method, we calculate the correlations of the sequences first and establish multivariate Markov chain models for those positively correlated sequences. The parameters are estimated by minimizing the error of prediction. We apply the method to demand predictions for a soft-drink company in Hong Kong. Numerical experiments are given to show the effectiveness of our proposed method.
Keywords
Markov processes; demand forecasting; minimisation; parameter estimation; Hong Kong; correlated sequences; demand predictions; error prediction minimization; multivariate Markov chain model; parameter estimation method; soft-drink company; Biological system modeling; Companies; Data models; Marketing and sales; Markov processes; Numerical models; Predictive models; Demand Prediction; Multivariate Markov Chain Model;
fLanguage
English
Publisher
ieee
Conference_Titel
Business Intelligence and Financial Engineering (BIFE), 2010 Third International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-7575-9
Type
conf
DOI
10.1109/BIFE.2010.39
Filename
5621744
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