Forecasting telecommunications data with linear models
AbstractFor telecommunication companies to successfully manage their business, companies rely on mapping future trends and usage patterns. However, the evolution of telecommunications technology and systems in the provision of services renders imperfections in telecommunications data and impinges on a company's' ability to properly evaluate and plan their business. International Telecommunication Union (ITU) Recommendation E.507 provides a selection of econometric models for forecasting these trends. However, no specific guidance is given. This paper evaluates whether simple extrapolation techniques in Recommendation E.507 can generate accurate forecasts. Standard forecast error statistics--mean absolute percentage error (MAPE), median absolute percentage error and percentage better--show the ARIMA, Holt and Holt-D models provide better forecasts than a random walk and other linear extrapolation methods.
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Bibliographic InfoArticle provided by Elsevier in its journal Telecommunications Policy.
Volume (Year): 31 (2007)
Issue (Month): 1 (February)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/30471/description#description
Other versions of this item:
- Madden, Gary G & Tan, Joachim, 2007. "Forecasting telecommunications data with linear models," MPRA Paper 14739, University Library of Munich, Germany.
- L96 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Telecommunications
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