Forecasting S-shaped diffusion processes via response modelling methodology
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DOI: 10.1057/palgrave.jors.2602187
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References listed on IDEAS
- Young, Peg & Ord, J. Keith, 1989. "Model selection and estimation for technological growth curves," International Journal of Forecasting, Elsevier, vol. 5(4), pages 501-513.
- Nigel Meade & Towhidul Islam, 1998. "Technological Forecasting---Model Selection, Model Stability, and Combining Models," Management Science, INFORMS, vol. 44(8), pages 1115-1130, August.
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Cited by:
- Chun, Young H., 2012. "Monte Carlo analysis of estimation methods for the prediction of customer response patterns in direct marketing," European Journal of Operational Research, Elsevier, vol. 217(3), pages 673-678.
- R Fildes & K Nikolopoulos & S F Crone & A A Syntetos, 2008. "Forecasting and operational research: a review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1150-1172, September.
- Chang, Ching-Ter & Lin, Teng-Chiao, 2009. "Interval goal programming for S-shaped penalty function," European Journal of Operational Research, Elsevier, vol. 199(1), pages 9-20, November.
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Keywords
diffusion processes; forecasting; inverse normalizing transformations; sigmoid curves; nonlinear regression; response modeling methodology;All these keywords.
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