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Forecasting Data Published at Irregular Time Intervals Using an Extension of Holt's Method

Author

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  • David J. Wright

    (Faculty of Administration, University of Ottawa, Ottawa, Ontario, K1N 6N5, Canada)

Abstract

In practice many data series contain observations at irregular times whereas most forecasting methods are restricted to the case of equal time intervals between data points. This paper provides extensions of Single Exponential Smoothing and Holt's Method to the case of irregularly spaced data and shows them to be highly efficient computationally. The new methods are applied to six published series, and their performance is analyzed via four error measures with respect to changes in the smoothing parameters.

Suggested Citation

  • David J. Wright, 1986. "Forecasting Data Published at Irregular Time Intervals Using an Extension of Holt's Method," Management Science, INFORMS, vol. 32(4), pages 499-510, April.
    • Handle: RePEc:inm:ormnsc:v:32:y:1986:i:4:p:499-510
    DOI: 10.1287/mnsc.32.4.499
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    Cited by:

    1. Michal Pešta, 2021. "Changepoint in Error-Prone Relations," Mathematics, MDPI, vol. 9(1), pages 1-25, January.
    2. G. E. Salcedo & R. F. Porto & S. Y. Roa & F. R. Momo, 2012. "A wavelet-based time-varying autoregressive model for non-stationary and irregular time series," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(11), pages 2313-2325, June.
    3. Kourentzes, Nikolaos & Athanasopoulos, George, 2021. "Elucidate structure in intermittent demand series," European Journal of Operational Research, Elsevier, vol. 288(1), pages 141-152.
    4. Bacchetti, Andrea & Saccani, Nicola, 2012. "Spare parts classification and demand forecasting for stock control: Investigating the gap between research and practice," Omega, Elsevier, vol. 40(6), pages 722-737.
    5. Pinçe, Çerağ & Turrini, Laura & Meissner, Joern, 2021. "Intermittent demand forecasting for spare parts: A Critical review," Omega, Elsevier, vol. 105(C).
    6. Jože Martin Rožanec & Blaž Fortuna & Dunja Mladenić, 2022. "Reframing Demand Forecasting: A Two-Fold Approach for Lumpy and Intermittent Demand," Sustainability, MDPI, vol. 14(15), pages 1-21, July.
    7. Altay, Nezih & Rudisill, Frank & Litteral, Lewis A., 2008. "Adapting Wright's modification of Holt's method to forecasting intermittent demand," International Journal of Production Economics, Elsevier, vol. 111(2), pages 389-408, February.
    8. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.

    More about this item

    Keywords

    forecasting/irregularly spaced data;

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