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An overview of short-term statistical forecasting methods
Department of Industrial Engineering, Arizona State University.
Department of Industrial Engineering, Arizona State University.ORCID iD: 0000-0003-4222-9631
Division of Mathematical and Natural Sciences, Arizona State University.
2006 (English)In: International Journal of Management Science and Engineering Management, ISSN 1750-9653, Vol. 1, no 1, p. 17-36Article in journal (Refereed) Published
Abstract [en]

An overview of statistical forecasting methodology is given, focusing on techniques appropriate to short- and medium-term forecasts. Topics include basic definitions and terminology, smoothing methods, ARIMA models, regression methods, dynamic regression models, and transfer functions. Techniques for evaluating and monitoring forecast performance are also summarized

Place, publisher, year, edition, pages
2006. Vol. 1, no 1, p. 17-36
National Category
Reliability and Maintenance
Research subject
Quality Technology and Management
Identifiers
URN: urn:nbn:se:ltu:diva-2652DOI: 10.1080/17509653.2006.10670994Local ID: 04da1438-81bd-4914-9ba7-72be42f0420aOAI: oai:DiVA.org:ltu-2652DiVA, id: diva2:975505
Note
Upprättat; 2006; 20150611 (andbra)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-03-16Bibliographically approved

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Kulahci, Murat

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