Madden, Gary G and Coble-Neal, Grant (2005): Forecasting international bandwidth capability. Published in: Journal of Forecasting No. 24 (2005): pp. 299-309.
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Abstract
M-competition studies provide a set of stylized recommendations to enhance forecast reliability. However, no single method dominates across series, leading to consideration of the relationship between selected data characteristics and the reliability of alternative forecast methods. This study conducts an analysis of predictive accuracy in relation to Internet bandwidth loads. Extrapolation techniques that perform best in M-competitions perform relatively poorly in predicting Internet bandwidth loads. Such performance is attributed to Internet bandwidth data exhibiting considerably less structure than M-competition data.
Item Type: | MPRA Paper |
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Original Title: | Forecasting international bandwidth capability |
Language: | English |
Keywords: | Bandwidth; forecast comparisons |
Subjects: | L - Industrial Organization > L9 - Industry Studies: Transportation and Utilities > L96 - Telecommunications C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods E - Macroeconomics and Monetary Economics > E1 - General Aggregative Models > E17 - Forecasting and Simulation: Models and Applications |
Item ID: | 10822 |
Depositing User: | Gary G Madden |
Date Deposited: | 29 Sep 2008 09:19 |
Last Modified: | 08 Oct 2019 04:55 |
References: | Armstrong JS, Collopy F. 1992. Error measures for generalizing about forecast methods: empirical comparisons. International Journal of Forecasting 8: 69–80. Clements MP, Hendry DF. 2001. Explaining the results of the M3 forecasting competition. International Journal of Forecasting 17: 537–584. Fildes R. 1992. The evaluation of extrapolative forecasting methods. International Journal of Forecasting 8: 81–98. Fildes R, Ord JK. 2002. Forecasting competitions—their role in improving forecasting practice and research. In A Companion to Economic Forecasting, Clements M, Hendry D (eds). Blackwell: Oxford. Fildes R, Hibon M, Makridakis S, Meade N. 1998. Generalising about univariate forecasting methods: further empirical evidence. International Journal of Forecasting 14: 339–358. Makridakis S, Hibon M. 1979. Accuracy of forecasting: an empirical investigation. Journal of the Royal Statistical Society, Series A 142(Part 2): 97–145. Makridakis S, Hibon M. 2000. The M3-competition: results, conclusions and implications. International Journal of Forecasting 16: 451–476. Makridakis S, Anderson A, Carbone R, Fildes R, Hibon M, Lewandowski R, Newton J, Parzen E, Winkler R. 1982. The accuracy of extrapolation (time series) methods: results of a forecasting competition. Journal of Forecasting 1: 111–153. Makridakis S, Chatfield C, Hibon M, Lawrence M, Mills T, Ord K, Simmons LF. 1993. The M-2 competition: a real-time judgmentally based forecasting study. International Journal of Forecasting 9: 5–23. Opinix. 2001. Internet Traffic Report. http://www.internettrafficreport.com. Parzen E. 1982. ARARMA models for time series analysis and forecasting. Journal of Forecasting 1: 67–82. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/10822 |