Research Article

ATA Method

Volume: 48 Number: 6 December 8, 2019
EN

ATA Method

Abstract

In this study, the forecasting accuracy of a new forecasting method that is alternative to two major forecasting approaches: exponential smoothing (ES) and ARIMA, will be evaluated. Using the results from the M3-competition, the forecasting performance of this method will be compared to not only these two major approaches but also to other successful methods derived from these two approaches with respect to simplicity and cost in addition to accuracy.

Keywords

References

  1. [1] S. Makridakis and M. Hibon, The M3-Competition: results, conclusions and implications, Int. J. Forecast, 16 (4), 451–476, 2000.
  2. [2] J. De Gooijer and R. Hyndman, 25 years of IIF time series forecasting: A selective review, Int. J. Forecast, 22 (3), 443–473, 2006.
  3. [3] P. Goodwin, The holt-winters approach to exponential smoothing: 50 years old and going strong, Foresight, 19, 30–33, 2010.
  4. [4] R. Hyndman, A. Koehler, R. Snyder and S. Grose, A state space framework for automatic forecasting using exponential smoothing methods, Int. J. Forecast, 13 (3), 439–454, 2002.
  5. [5] R. Hyndman, A. Koehler, J. Ord and R. Snyder, Forecasting with exponential smoothing: the state space approach, Springer-Verlag, 2008.
  6. [6] R. Hyndman and G. Athanasopoulos, Forecasting: principles and practice, OTexts, 2014.
  7. [7] C. Pegels, On startup or learning curves: An expanded view, AIIE Transactions, 1 (3), 216–222, 1969.
  8. [8] E. Gardner Jr and E. McKenzie, Forecasting trends in time series, Management Science, 31 (10), 1237–1246, 1985.

Details

Primary Language

English

Subjects

Mathematical Sciences

Journal Section

Research Article

Publication Date

December 8, 2019

Submission Date

September 18, 2018

Acceptance Date

July 18, 2019

Published in Issue

Year 2019 Volume: 48 Number: 6

APA
Yapar, G., Taylan Selamlar, H., Capar, S., & Yavuz, İ. (2019). ATA Method. Hacettepe Journal of Mathematics and Statistics, 48(6), 1838-1844. https://doi.org/10.15672/hujms.461032
AMA
1.Yapar G, Taylan Selamlar H, Capar S, Yavuz İ. ATA Method. Hacettepe Journal of Mathematics and Statistics. 2019;48(6):1838-1844. doi:10.15672/hujms.461032
Chicago
Yapar, Guckan, Hanife Taylan Selamlar, Sedat Capar, and İdil Yavuz. 2019. “ATA Method”. Hacettepe Journal of Mathematics and Statistics 48 (6): 1838-44. https://doi.org/10.15672/hujms.461032.
EndNote
Yapar G, Taylan Selamlar H, Capar S, Yavuz İ (December 1, 2019) ATA Method. Hacettepe Journal of Mathematics and Statistics 48 6 1838–1844.
IEEE
[1]G. Yapar, H. Taylan Selamlar, S. Capar, and İ. Yavuz, “ATA Method”, Hacettepe Journal of Mathematics and Statistics, vol. 48, no. 6, pp. 1838–1844, Dec. 2019, doi: 10.15672/hujms.461032.
ISNAD
Yapar, Guckan - Taylan Selamlar, Hanife - Capar, Sedat - Yavuz, İdil. “ATA Method”. Hacettepe Journal of Mathematics and Statistics 48/6 (December 1, 2019): 1838-1844. https://doi.org/10.15672/hujms.461032.
JAMA
1.Yapar G, Taylan Selamlar H, Capar S, Yavuz İ. ATA Method. Hacettepe Journal of Mathematics and Statistics. 2019;48:1838–1844.
MLA
Yapar, Guckan, et al. “ATA Method”. Hacettepe Journal of Mathematics and Statistics, vol. 48, no. 6, Dec. 2019, pp. 1838-44, doi:10.15672/hujms.461032.
Vancouver
1.Guckan Yapar, Hanife Taylan Selamlar, Sedat Capar, İdil Yavuz. ATA Method. Hacettepe Journal of Mathematics and Statistics. 2019 Dec. 1;48(6):1838-44. doi:10.15672/hujms.461032

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