Quality Quandaries- Time Series Model Selection and Parsimony

Søren Bisgaard, Murat Kulahci

    Research output: Contribution to journalJournal articleResearchpeer-review


    Some of the issues involved in selecting adequate models for time series data are discussed using an example concerning the number of users of an Internet server. The process of selecting an appropriate model is subjective and requires experience and judgment. The authors believe an important consideration in model selection should be parameter parsimony. They favor the use of parsimonious mixed ARMA models, noting that research has shown that a model building strategy that considers only autoregressive representations will lead to non-parsimonious models and to loss of forecasting accuracy.
    Original languageEnglish
    JournalQuality Engineering
    Issue number3
    Pages (from-to)341-353
    Publication statusPublished - 2009


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