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Title: Holt-Winters method with general seasonality (English)
Author: Hanzák, Tomáš
Language: English
Journal: Kybernetika
ISSN: 0023-5954
Volume: 48
Issue: 1
Year: 2012
Pages: 1-15
Summary lang: English
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Category: math
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Summary: The paper suggests a generalization of widely used Holt-Winters smoothing and forecasting method for seasonal time series. The general concept of seasonality modeling is introduced both for the additive and multiplicative case. Several special cases are discussed, including a linear interpolation of seasonal indices and a usage of trigonometric functions. Both methods are fully applicable for time series with irregularly observed data (just the special case of missing observations was covered up to now). Moreover, they sometimes outperform the classical Holt-Winters method even for regular time series. A simulation study and real data examples compare the suggested methods with the classical one. (English)
Keyword: exponential smoothing
Keyword: Holt--Winters method
Keyword: irregular time series
Keyword: seasonal indices
Keyword: trigonometric functions
MSC: 60G35
MSC: 62M10
MSC: 62M20
MSC: 65D10
idZBL: Zbl 1244.62132
idMR: MR2932925
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Date available: 2012-03-05T08:25:15Z
Last updated: 2013-09-22
Stable URL: http://hdl.handle.net/10338.dmlcz/142058
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Reference: [1] M. Aldrin, E. Damsleth: Forecasting non-seasonal time series with missing observations..J. Forecasting 8 (1989), 97-116. 10.1002/for.3980080204
Reference: [2] C. Chatfield, M. Yar: Holt-Winters forecasting: some practical issues..The Statistician 37 (1988), 129-140. 10.2307/2348687
Reference: [3] T. Cipra, T. Hanzák: Exponential smoothing for irregular time series..Kybernetika 44 (2008), 385-399. Zbl 1154.62363, MR 2436039
Reference: [4] T. Cipra, J. Trujillo, A. Rubio: Holt-Winters method with missing observations..Management Sci. 41 (1995), 174-178. Zbl 0829.90034, 10.1287/mnsc.41.1.174
Reference: [5] E. S. Gardner: Exponential smoothing: The state of the art..J. Forecasting 4 (1985), 1-28. 10.1002/for.3980040103
Reference: [6] E. S. Gardner: Exponential smoothing: The state of the art - Part II..Internat. J. Forecasting 22 (2006), 637-666. 10.1016/j.ijforecast.2006.03.005
Reference: [7] T. Hanzák: Improved Holt method for irregular time series..In: WDS'08 Proc. Contributed Papers, Part I - Mathematics and Computer Sciences, Matfyzpress, Prague 2008, pp. 62-67.
Reference: [8] C. C. Holt: Forecasting seasonals and trends by exponentially weighted moving averages..Internat. J. Forecasting 20 (2004), 5-10. 10.1016/j.ijforecast.2003.09.015
Reference: [9] R. J. Hyndman: Time Series Data Library, www.robhyndman.info/TSDL..Accessed on 26 June 2010.
Reference: [10] R. J. Hyndman, A. B. Koehler, R. D. Snyder, S. Grose: A state space framework for automatic forecasting using exponential smoothing methods..Internat. J. Forecasting 18 (2002), 439-454. 10.1016/S0169-2070(01)00110-8
Reference: [11] T. Ratinger: Seasonal time series with missing observations..Appl. Math. 41 (1996), 41-55. Zbl 0888.62097, MR 1365138
Reference: [12] J. W. Taylor: Short-term electricity demand forecasting using double seasonal exponential smoothing..J. Oper. Res. Soc. 54 (2003), 799-805. Zbl 1097.91541, 10.1057/palgrave.jors.2601589
Reference: [13] J. W. Taylor: A comparison of univariate time series methods for forecasting intraday arrivals at a call center..Management Sci. 54 (2008), 253-265. Zbl 1232.90214, 10.1287/mnsc.1070.0786
Reference: [14] P. R. Winters: Forecasting sales by exponentially weighted moving averages..Management Sci. 6 (1960), 324-342. Zbl 0995.90562, MR 0112740, 10.1287/mnsc.6.3.324
Reference: [15] D. J. Wright: Forecasting data published at irregular time intervals using extension of Holt's method..Management Sci. 32 (1986), 499-510. 10.1287/mnsc.32.4.499
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