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Holt-Winters Method with Missing Observations

Author

Listed:
  • Tomáv{s} Cipra

    (Department of Statistics, Charles University of Prague, Sokolovská 83, 18600 Prague 8, Czechoslovakia)

  • José Trujillo

    (Department of Mathematics, University of Extremadura, 10071 Cáceres, Spain)

  • Asunción Robio

    (Department of Mathematics, University of Extremadura, 10071 Cáceres, Spain)

Abstract

The paper presents a simple procedure for interpolating, smoothing, and predicting in seasonal time series with missing observations. The approach suggested by Wright (Wright, D. J. 1986. Forecasting data published at irregular time intervals using extension of Holt's method. Management Sci. 32 499--510.) for the Holt's method with nonseasonal data published at irregular time intervals is extended to the Holt-Winters method in the seasonal case. Numerical examples demonstrate the procedure.

Suggested Citation

  • Tomáv{s} Cipra & José Trujillo & Asunción Robio, 1995. "Holt-Winters Method with Missing Observations," Management Science, INFORMS, vol. 41(1), pages 174-178, January.
    • Handle: RePEc:inm:ormnsc:v:41:y:1995:i:1:p:174-178
    DOI: 10.1287/mnsc.41.1.174
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    Cited by:

    1. 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.
    2. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.

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