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Quality quandaries: Time series model selection and parsimony
Isenberg School of Management, University of Massachusetts Amherst.
Department of Informatics and Mathematical Modelling, Technical University of Denmark.ORCID iD: 0000-0003-4222-9631
2009 (English)In: Quality Engineering, ISSN 0898-2112, E-ISSN 1532-4222, Vol. 21, no 3, p. 341-353Article in journal (Refereed) Published
Abstract [en]

Choosing an adequate model for a certain set of data is considered to be one of the more difficult tasks in time series analysis as experienced analysts are also having a hard time selecting such appropriate model. Thus, one popular approach have been discussed with the use of certain numerical criteria which is believed to be a useful input for the decision making process. However, using this technique solely is also not advisable on choosing a model but the use of judgement and the use of information criteria are more preferred. Specifically, the use of parsimonious mixed autoregressive model (ARMA) is more favorable to be used as it considers the context of the model as well as illustrating what is trying to be modeled and what model is to be used.

Place, publisher, year, edition, pages
2009. Vol. 21, no 3, p. 341-353
National Category
Reliability and Maintenance
Research subject
Quality Technology and Management
Identifiers
URN: urn:nbn:se:ltu:diva-2440DOI: 10.1080/08982110903025197ISI: 000208165800015Scopus ID: 2-s2.0-70749134822Local ID: 0112ca9a-ba7d-4345-a66b-a3f24165e4e2OAI: oai:DiVA.org:ltu-2440DiVA, id: diva2:975292
Note
Upprättat; 2009; 20150527 (andbra)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2023-05-08Bibliographically approved

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Kulahci, Murat

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