IMPORTANCE OF INITIAL VALUE IN EXPONENTIAL SMOOTHING METHODS

Öz

ÜSTEL DÜZLEŞTİRME YÖNTEMLERİNDE BAŞLANGIÇ DEĞERİNİN ÖNEMİ

Öz

Üstel düzleştirme çeşitli zaman serisi verileri için yaygın olarak kullanılan popüler bir tahmin yöntemidir. Üstel düzleştirme ile ilgili iki önemli problem mevcuttur. Birincisi, düzleştirme sabitinin değerine karar vermek. İkincisi de başlangıç değerini belirlemektir. Bu çalışmada başlangıç değerinin önemi ve tahmin üzerindeki etkisi araştırılmış ve araştırmacılara yardımcı olmak amacıyla bir çapraz tablo oluşturulmuştur.

Anahtar Kelimeler: Üstel Düzleştirme, Basit Üstel Düzleştirme, Başlangıç Değeri.

IMPORTANCE OF INITIAL VALUE IN EXPONENTIAL SMOOTHING METHODS

Öz

Exponential smoothing is a very popular forecasting method for a wide range of time series data. There are two problems with exponential smoothing. First one is choosing smoothing constant. And second one is how to get initial value. In this paper importance of initial value and effects of it on the forecast is investigated and a cross table is constructed to help forecasters.

Keywords: Exponential Smoothing, Simple Exponential Smoothing, Initial Value.

Kaynakça

1. Abraham, B. and Ledolter, J. (1983). Statistical methods for forecasting. New York: John Wiley and Sons.
2. Armstrong, J. S. and Collopy, F. (1992). Error measures for generalizing about forecasting methods: Empirical comparisons. International Journal of Forecasting, 8 (1): 69-80.
3. Armstrong, J. S. and Collopy, F. (1993). Causal forces: Structuring knowledge for time series extrapolation. Journal of Forecasting, 12 (2): 103-115.
4. Brown, R. G. (1959). Statistical Smoothing for inventory control. New York: McGraw-Hill.
5. Brown, R. G. (1964). Smoothing, forecasting and prediction of discrete time series. NJ: Prentice-Hall.
6. Clemen, R. T. (1989). Combining forecasts: A review and annotated bibliography. International Journal of Forecasting, 5 (4): 559-583.
7. Cohen, G. D. (1966). Bayesian adjustment of sales forecasts in multi-item inventory control system. Journal of Industrial Engineering, 17: 474-479.
8. Fildes, R., Hibon, M., Makridakis, S. and Meade, N. (1998). Generalising about univariate forecasting methods: Further empirical evidence. International Journal of Forecasting, 14 (3): 339-358.

9. Gardner, Jr. E. S. (1985). Exponential smoothing: The state of the art. Journal of Forecasting, 4 (1): 1-28.
10. Gardner, Jr. E. S. (2006). Exponential smoothing: The state of the art - Part II. International Journal of Forecasting, 22 (4): 637-666.
11. Gass, S. I. and Harris, C. M. (Eds.) (2000). Encyclopedia of operations research and management science. Dordrecht: Kluwer Academic Publishers.
12. Geurts, M. D. and Kelly, J. P. (1986). Forecasting retail sales using alternative models. International Journal of Forecasting, 2 (3): 261-272.
13. Hill, G. and Fildes, R. (1984). The accuracy of extrapolation methods: An automatic Box–Jenkins package SIFT. Journal of Forecasting, 3 (3): 319-323.
14. Holt, C. C. (1957). Forecasting seasonals and trends by exponentially weighted moving averages, ONR Memorandum. Pitssburgh, PA: Carnegie Institute of Technology.
15. Holt, C. C, Modigliani, F., Muth, J. F. and Simon, H. (1969). Planning production, inventories, and the work force. NJ: Prentice Hall.
16. Johnson, L. A. and Montgomery, D. C. (1974). Operations research in production planning, scheduling, and inventory control. New York: Wiley.
17. Koehler, A. B. and Murphree, E. S. (1988). A comparison of results from state space forecasting with forecasts from the Makridakis competition. International Journal of Forecasting, 4 (1): 45-55.
18. Ledolter, J. and Abraham, B. (1984). Some comments on the initialization of exponential smoothing. Journal of Forecasting, 3 (1): 79-84.
19. Lusk, E. J. and Neves, J. S. (1984). A comparative ARIMA analysis of the 111 series of the Makridakis competition. Journal of Forecasting, 3 (3): 329-332.
20. Makridakis, S., Hibon, M. and Moser, C. (1979). Accuracy of forecasting: An empirical investigation. Journal of the Royal Statistical Society: Series A (General), 142 (2): 97-145.
21. Makridakis, S., Andersen A., Carbone R., Fildes, R., Hibon, M., Lewandowski, R., Newton, J., Parzen, E. and Winkler, R. (1982). The Accuracy of extrapolation (time series) methods: Results of a forecasting competition. Journal of Forecasting, 1 (2): 111-153.
22. Pegels, C. C. (1969). Exponential forecasting: Some new variations. Management Science. 15 (5): 311-315.
23. Roberts, S. A. (1982). A general class of Holt–Winters type forecasting models. Management Science, 28 (7): 808-820.
24. Taylor, S. G. (1981). Initialization of exponential smoothing forecasts. AIIE Transactions, 13 (3): 199-205.
25. Winters, P. R. (1960). Forecasting sales by exponentially weighted moving averages. Management Science. 6 (3): 324-342.
26. Xie, M., Hong, G. Y. and Wohlin, C. (1997) A study of the exponential smoothing technique in software reliability growth prediction. Quality and Reliability Engineering International, 13 (6): 347-353.