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Model selection in univariate time series forecasting using discriminant analysis

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  • Shah, Chandra

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  • Shah, Chandra, 1997. "Model selection in univariate time series forecasting using discriminant analysis," International Journal of Forecasting, Elsevier, vol. 13(4), pages 489-500, December.
    • Handle: RePEc:eee:intfor:v:13:y:1997:i:4:p:489-500
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    References listed on IDEAS

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    1. Robert Fildes, 1989. "Evaluation of Aggregate and Individual Forecast Method Selection Rules," Management Science, INFORMS, vol. 35(9), pages 1056-1065, September.
    2. Flores, Benito E., 1986. "Use of the sign test to supplement the percentage better statistic," International Journal of Forecasting, Elsevier, vol. 2(4), pages 477-489.
    3. J. P. Royston, 1982. "The W Test for Normality," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 31(2), pages 176-180, June.
    4. Makridakis, Spyros, 1986. "The art and science of forecasting An assessment and future directions," International Journal of Forecasting, Elsevier, vol. 2(1), pages 15-39.
    5. Armstrong, J. Scott & Collopy, Fred, 1992. "Error measures for generalizing about forecasting methods: Empirical comparisons," International Journal of Forecasting, Elsevier, vol. 8(1), pages 69-80, June.
    6. Thompson, Patrick A., 1990. "An MSE statistic for comparing forecast accuracy across series," International Journal of Forecasting, Elsevier, vol. 6(2), pages 219-227, July.
    7. Fildes, Robert, 1992. "The evaluation of extrapolative forecasting methods," International Journal of Forecasting, Elsevier, vol. 8(1), pages 81-98, June.
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    Cited by:

    1. Robert Fildes & Gary Madden & Joachim Tan, 2007. "Optimal forecasting model selection and data characteristics," Applied Financial Economics, Taylor & Francis Journals, vol. 17(15), pages 1251-1264.
    2. Wallström, Peter & Segerstedt, Anders, 2010. "Evaluation of forecasting error measurements and techniques for intermittent demand," International Journal of Production Economics, Elsevier, vol. 128(2), pages 625-636, December.
    3. Dimitrios Sarris & Evangelos Spiliotis & Vassilios Assimakopoulos, 2020. "Exploiting resampling techniques for model selection in forecasting: an empirical evaluation using out-of-sample tests," Operational Research, Springer, vol. 20(2), pages 701-721, June.
    4. Kang, Yanfei & Spiliotis, Evangelos & Petropoulos, Fotios & Athiniotis, Nikolaos & Li, Feng & Assimakopoulos, Vassilios, 2021. "Déjà vu: A data-centric forecasting approach through time series cross-similarity," Journal of Business Research, Elsevier, vol. 132(C), pages 719-731.
    5. Thiyanga S. Talagala & Feng Li & Yanfei Kang, 2019. "Feature-based Forecast-Model Performance Prediction," Monash Econometrics and Business Statistics Working Papers 21/19, Monash University, Department of Econometrics and Business Statistics.
    6. Fildes, Robert & Petropoulos, Fotios, 2015. "Simple versus complex selection rules for forecasting many time series," Journal of Business Research, Elsevier, vol. 68(8), pages 1692-1701.
    7. Fildes, Robert & Petropoulos, Fotios, 2013. "An evaluation of simple forecasting model selection rules," MPRA Paper 51772, University Library of Munich, Germany.
    8. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
    9. Petropoulos, Fotios & Makridakis, Spyros & Assimakopoulos, Vassilios & Nikolopoulos, Konstantinos, 2014. "‘Horses for Courses’ in demand forecasting," European Journal of Operational Research, Elsevier, vol. 237(1), pages 152-163.
    10. Fotios Petropoulos & Enno Siemsen, 2023. "Forecast Selection and Representativeness," Management Science, INFORMS, vol. 69(5), pages 2672-2690, May.
    11. Talagala, Thiyanga S. & Li, Feng & Kang, Yanfei, 2022. "FFORMPP: Feature-based forecast model performance prediction," International Journal of Forecasting, Elsevier, vol. 38(3), pages 920-943.
    12. Marahaj, E.A. & Inder, B., 1999. "Forecasting Time Series from Clusters," Monash Econometrics and Business Statistics Working Papers 9/99, Monash University, Department of Econometrics and Business Statistics.
    13. Thiyanga S Talagala & Rob J Hyndman & George Athanasopoulos, 2018. "Meta-learning how to forecast time series," Monash Econometrics and Business Statistics Working Papers 6/18, Monash University, Department of Econometrics and Business Statistics.
    14. Graff, Mario & Peña, Rafael & Medina, Aurelio & Escalante, Hugo Jair, 2014. "Wind speed forecasting using a portfolio of forecasters," Renewable Energy, Elsevier, vol. 68(C), pages 550-559.

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