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Beyond accuracy: Comparison of criteria used to select forecasting methods


  • Yokuma, J. Thomas
  • Armstrong, J. Scott


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Suggested Citation

  • Yokuma, J. Thomas & Armstrong, J. Scott, 1995. "Beyond accuracy: Comparison of criteria used to select forecasting methods," International Journal of Forecasting, Elsevier, vol. 11(4), pages 591-597, December.
  • Handle: RePEc:eee:intfor:v:11:y:1995:i:4:p:591-597

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    References listed on IDEAS

    1. Collopy, Fred & Armstrong, J. Scott, 1992. "Expert opinions about extrapolation and the mystery of the overlooked discontinuities," International Journal of Forecasting, Elsevier, vol. 8(4), pages 575-582, December.
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    Cited by:

    1. Che-Jung Chang & Liping Yu & Peng Jin, 2016. "A mega-trend-diffusion grey forecasting model for short-term manufacturing demand," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(12), pages 1439-1445, December.
    2. Che-Jung Chang & Jan-Yan Lin & Peng Jin, 2017. "A grey modeling procedure based on the data smoothing index for short-term manufacturing demand forecast," Computational and Mathematical Organization Theory, Springer, vol. 23(3), pages 409-422, September.
    3. Shuyun Ren & Hau-Ling Chan & Pratibha Ram, 2017. "A Comparative Study on Fashion Demand Forecasting Models with Multiple Sources of Uncertainty," Annals of Operations Research, Springer, vol. 257(1), pages 335-355, October.
    4. Eksoz, Can & Mansouri, S. Afshin & Bourlakis, Michael & Önkal, Dilek, 2019. "Judgmental adjustments through supply integration for strategic partnerships in food chains," Omega, Elsevier, vol. 87(C), pages 20-33.
    5. Li, Der-Chiang & Chang, Che-Jung & Chen, Chien-Chih & Chen, Wen-Chih, 2012. "Forecasting short-term electricity consumption using the adaptive grey-based approach—An Asian case," Omega, Elsevier, vol. 40(6), pages 767-773.
    6. Wu, Chunying & Wang, Jianzhou & Chen, Xuejun & Du, Pei & Yang, Wendong, 2020. "A novel hybrid system based on multi-objective optimization for wind speed forecasting," Renewable Energy, Elsevier, vol. 146(C), pages 149-165.
    7. Robert Fildes & Paul Goodwin, 2007. "Against Your Better Judgment? How Organizations Can Improve Their Use of Management Judgment in Forecasting," Interfaces, INFORMS, vol. 37(6), pages 570-576, December.
    8. Emrouznejad, Ali & Rostami-Tabar, Bahman & Petridis, Konstantinos, 2016. "A novel ranking procedure for forecasting approaches using Data Envelopment Analysis," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 235-243.
    9. Sinan Gönül & Dilek Önkal & Paul Goodwin, 2009. "Expectations, use and judgmental adjustment of external financial and economic forecasts: an empirical investigation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(1), pages 19-37.
    10. Chang, Che-Jung & Li, Der-Chiang & Huang, Yi-Hsiang & Chen, Chien-Chih, 2015. "A novel gray forecasting model based on the box plot for small manufacturing data sets," Applied Mathematics and Computation, Elsevier, vol. 265(C), pages 400-408.
    11. Nada R. Sanders & Karl B. Manrodt, 2003. "Forecasting Software in Practice: Use, Satisfaction, and Performance," Interfaces, INFORMS, vol. 33(5), pages 90-93, October.
    12. Veiga, Claudimar Pereira da & Veiga, Cássia Rita Pereira da & Puchalski, Weslly & Coelho, Leandro dos Santos & Tortato, Ubiratã, 2016. "Demand forecasting based on natural computing approaches applied to the foodstuff retail segment," Journal of Retailing and Consumer Services, Elsevier, vol. 31(C), pages 174-181.
    13. Williams, Dan W. & Miller, Don, 1999. "Level-adjusted exponential smoothing for modeling planned discontinuities1," International Journal of Forecasting, Elsevier, vol. 15(3), pages 273-289, July.
    14. JS Armstrong, 2004. "Forecasting for Environmental Decision Making," General Economics and Teaching 0412023, University Library of Munich, Germany.
    15. Guo, Zhenhai & Zhao, Jing & Zhang, Wenyu & Wang, Jianzhou, 2011. "A corrected hybrid approach for wind speed prediction in Hexi Corridor of China," Energy, Elsevier, vol. 36(3), pages 1668-1679.
    16. repec:aaa:journl:v:3:y:1999:i:1:p:87-100 is not listed on IDEAS
    17. Stefan Rayer, 2007. "Population forecast accuracy: does the choice of summary measure of error matter?," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 26(2), pages 163-184, April.
    18. Smith, Stanley K., 1997. "Further thoughts on simplicity and complexity in population projection models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 557-565, December.
    19. JS Armstrong & Fred Collopy, 2004. "Integration of Statistical Methods and Judgment for Time Series," General Economics and Teaching 0412024, University Library of Munich, Germany.
    20. Xu, Bing & Ouenniche, Jamal, 2012. "A data envelopment analysis-based framework for the relative performance evaluation of competing crude oil prices' volatility forecasting models," Energy Economics, Elsevier, vol. 34(2), pages 576-583.
    21. Che-Jung Chang & Jan-Yan Lin & Peng Jin, 0. "A grey modeling procedure based on the data smoothing index for short-term manufacturing demand forecast," Computational and Mathematical Organization Theory, Springer, vol. 0, pages 1-14.
    22. Adya, Monica & Collopy, Fred & Armstrong, J. Scott & Kennedy, Miles, 2001. "Automatic identification of time series features for rule-based forecasting," International Journal of Forecasting, Elsevier, vol. 17(2), pages 143-157.
    23. Zhou, P. & Ang, B.W. & Poh, K.L., 2006. "A trigonometric grey prediction approach to forecasting electricity demand," Energy, Elsevier, vol. 31(14), pages 2839-2847.
    24. Khim-Sen Liew & Kian-Ping Lim & Chee-Keong Choong, 2003. "On The Forecastability Of Asean-5 Stock Markets Returns Using Time Series Models," Finance 0307012, University Library of Munich, Germany.

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