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A note on the Robust Trend and ARARMA methodologies used in the M3 Competition

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  • Meade, Nigel

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  • Meade, Nigel, 2000. "A note on the Robust Trend and ARARMA methodologies used in the M3 Competition," International Journal of Forecasting, Elsevier, vol. 16(4), pages 517-519.
    • Handle: RePEc:eee:intfor:v:16:y:2000:i:4:p:517-519
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    1. Fildes, Robert & Hibon, Michele & Makridakis, Spyros & Meade, Nigel, 1998. "Generalising about univariate forecasting methods: further empirical evidence," International Journal of Forecasting, Elsevier, vol. 14(3), pages 339-358, September.
    2. Grambsch, Patricia & Stahel, Werner A., 1990. "Forecasting demand for special telephone services: A case study," International Journal of Forecasting, Elsevier, vol. 6(1), pages 53-64.
    3. Meade, Nigel & Smith, Ian Md, 1985. "ARARMA vs ARIMA--A study of the benefits of a new approach to forecasting," Omega, Elsevier, vol. 13(6), pages 519-534.
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    Cited by:

    1. Miller, Don M. & Williams, Dan, 2003. "Shrinkage estimators of time series seasonal factors and their effect on forecasting accuracy," International Journal of Forecasting, Elsevier, vol. 19(4), pages 669-684.
    2. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    3. Feridun, M. & Adebiyi, M.A., 2006. "Forecasting Inflation in Developing Economies: The Case of Nigeria, 1986-1998," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 3(1), pages 55-84.
    4. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.
    5. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.

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