Statistical model selection based on Bayes decision theory and its application to change detection problem

Masayuki Goto, Shigeichi Hirasawa

    Research output: Contribution to journalArticle

    1 Citation (Scopus)

    Abstract

    The statistical model selection problems are discussed, and the criterion based on the Bayes decision theory for the detection of the true model is derived. We propose a new Bayesian model selection scheme, which can detect the change points of the parameter of the information source and also estimate each unknown parameter. In this paper, we formulate the Bayes optimal solution of the change detection problem, and analyze its property of the consistency.

    Original languageEnglish
    Pages (from-to)629-638
    Number of pages10
    JournalInternational Journal of Production Economics
    Volume60
    DOIs
    Publication statusPublished - 1999 Apr 20

    Fingerprint

    Decision theory
    Statistical Models
    Change detection
    Statistical model
    Model selection
    Information sources
    Change point
    Optimal solution
    Bayesian model

    ASJC Scopus subject areas

    • Economics and Econometrics
    • Industrial and Manufacturing Engineering

    Cite this

    Statistical model selection based on Bayes decision theory and its application to change detection problem. / Goto, Masayuki; Hirasawa, Shigeichi.

    In: International Journal of Production Economics, Vol. 60, 20.04.1999, p. 629-638.

    Research output: Contribution to journalArticle

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