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A Mixture-Model Approach to Combining Forecasts

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Author Info

  • LeSage, James P
  • Magura, Michael

Abstract

A multiprocess mixture-model approach to combining forecasts from alternative sources is proposed. This approach extends the Granger-Ramanathan method by allowing the weights used in producing the combination forecast to vary over time. In addition, the procedure discounts outlying data points that arise during time periods when all of the competing forecasts miss the mark. An empirical comparison with traditional and more recently proposed.combination methods demonstrates that the proposed methodology outperforms these.

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Bibliographic Info

Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 10 (1992)
Issue (Month): 4 (October)
Pages: 445-52

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Handle: RePEc:bes:jnlbes:v:10:y:1992:i:4:p:445-52

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Cited by:
  1. Chan, Chi Kin & Kingsman, Brian G. & Wong, H., 1999. "The value of combining forecasts in inventory management - a case study in banking," European Journal of Operational Research, Elsevier, vol. 117(2), pages 199-210, September.
  2. Timmermann, Allan G, 2005. "Forecast Combinations," CEPR Discussion Papers 5361, C.E.P.R. Discussion Papers.
  3. de Menezes, Lilian M. & W. Bunn, Derek & Taylor, James W., 2000. "Review of guidelines for the use of combined forecasts," European Journal of Operational Research, Elsevier, vol. 120(1), pages 190-204, January.

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