Computing interval-valued statistical characteristics: What is the stumbling block for reliability applications?

Igor Kozine, V.G. Krymsky

    Research output: Contribution to journalJournal articleResearchpeer-review

    Abstract

    The application of interval-valued statistical models is often hindered by the rapid growth in imprecision that occurs when intervals are propagated through models. Is this deficiency inherent in the models? If so, what is the underlying cause of imprecision in mathematical terms? What kind of additional information can be incorporated to make the bounds tighter? The present paper gives an account of the source of this imprecision that prevents interval-valued statistical models from being widely applied. Firstly, the mathematical approach to building interval-valued models (discrete and continuous) is delineated. Secondly, a degree of imprecision is demonstrated on some simple reliability models. Thirdly, the root mathematical cause of sizeable imprecision is elucidated and, finally, a method of making the intervals tighter is described. A number of examples are given throughout the paper.
    Original languageEnglish
    JournalInternational Journal of General Systems
    Volume38
    Issue number5
    Pages (from-to)547-565
    ISSN0308-1079
    DOIs
    Publication statusPublished - 2009

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