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Determining when to update the weights in combined forecasts for product demand--an application of the CUSUM technique

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  • Chan, Chi Kin
  • Kingsman, Brian G.
  • Wong, H.

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  • Chan, Chi Kin & Kingsman, Brian G. & Wong, H., 2004. "Determining when to update the weights in combined forecasts for product demand--an application of the CUSUM technique," European Journal of Operational Research, Elsevier, vol. 153(3), pages 757-768, March.
    • Handle: RePEc:eee:ejores:v:153:y:2004:i:3:p:757-768
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    References listed on IDEAS

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    1. Chan, Chi Kin & Kingsman, Brian G. & Wong, H., 1999. "The value of combining forecasts in inventory management - a case study in banking," European Journal of Operational Research, Elsevier, vol. 117(2), pages 199-210, September.
    2. Deutsch, Melinda & Granger, Clive W. J. & Terasvirta, Timo, 1994. "The combination of forecasts using changing weights," International Journal of Forecasting, Elsevier, vol. 10(1), pages 47-57, June.
    3. Granger, C. W. J. & Newbold, Paul, 1986. "Forecasting Economic Time Series," Elsevier Monographs, Elsevier, edition 2, number 9780122951831 edited by Shell, Karl.
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    Cited by:

    1. Yi-Chung Hu, 2023. "Tourism combination forecasting using a dynamic weighting strategy with change-point analysis," Current Issues in Tourism, Taylor & Francis Journals, vol. 26(14), pages 2357-2374, July.
    2. Zhang, Feng, 2007. "An application of vector GARCH model in semiconductor demand planning," European Journal of Operational Research, Elsevier, vol. 181(1), pages 288-297, August.
    3. Chan, Chi Kin & Witt, Stephen F. & Lee, Y.C.E. & Song, H., 2010. "Tourism forecast combination using the CUSUM technique," Tourism Management, Elsevier, vol. 31(6), pages 891-897.
    4. Rendon-Sanchez, Juan F. & de Menezes, Lilian M., 2019. "Structural combination of seasonal exponential smoothing forecasts applied to load forecasting," European Journal of Operational Research, Elsevier, vol. 275(3), pages 916-924.
    5. Laleh Parviz & Kabir Rasouli & Ali Torabi Haghighi, 2023. "Improving Hybrid Models for Precipitation Forecasting by Combining Nonlinear Machine Learning Methods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(10), pages 3833-3855, August.
    6. Zhao, Weigang & Wang, Jianzhou & Lu, Haiyan, 2014. "Combining forecasts of electricity consumption in China with time-varying weights updated by a high-order Markov chain model," Omega, Elsevier, vol. 45(C), pages 80-91.

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