Calibration in a Bayesian modelling framework

M.J.W. Jansen, T.H.J. Hagenaars

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

    Abstract

    Bayesian statistics may constitute the core of a consistent and comprehensive framework for the statistical aspects of modelling complex processes that involve many parameters whose values are derived from many sources. Bayesian statistics holds great promises for model calibration, provides the perfect starting point for uncertainty analysis and provides an excellent starting point for decision support. The purpose of this paper is to draw attention to problems and possible solutions. It is not our intention to introduce ready-for-use methods
    Original languageEnglish
    Title of host publicationBayesian Statistics and Quality Modelling in the Agro-Food Production Chain
    Editorsvan Boekel, A. Stein, van Bruggen
    Place of PublicationDordrecht
    Pages47-55
    Number of pages2
    Publication statusPublished - 2004

    Publication series

    NameWageningen UR Frontis series
    PublisherKluwer
    Numbervol. 3

    Fingerprint

    Bayesian Statistics
    Bayesian Modeling
    Calibration
    Uncertainty Analysis
    Model Calibration
    Decision Support
    Modeling
    Framework

    Keywords

    • bayesian theory
    • monte carlo method
    • mathematical models
    • calibration
    • uncertainty
    • decision support systems

    Cite this

    Jansen, M. J. W., & Hagenaars, T. H. J. (2004). Calibration in a Bayesian modelling framework. In V. Boekel, A. Stein, & V. Bruggen (Eds.), Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain (pp. 47-55). (Wageningen UR Frontis series; No. vol. 3). Dordrecht.
    Jansen, M.J.W. ; Hagenaars, T.H.J. / Calibration in a Bayesian modelling framework. Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain. editor / van Boekel ; A. Stein ; van Bruggen. Dordrecht, 2004. pp. 47-55 (Wageningen UR Frontis series; vol. 3).
    @inbook{354c553650364301b91ffb3630688a39,
    title = "Calibration in a Bayesian modelling framework",
    abstract = "Bayesian statistics may constitute the core of a consistent and comprehensive framework for the statistical aspects of modelling complex processes that involve many parameters whose values are derived from many sources. Bayesian statistics holds great promises for model calibration, provides the perfect starting point for uncertainty analysis and provides an excellent starting point for decision support. The purpose of this paper is to draw attention to problems and possible solutions. It is not our intention to introduce ready-for-use methods",
    keywords = "bayesiaanse theorie, monte carlo-methode, wiskundige modellen, kalibratie, onzekerheid, beslissingsondersteunende systemen, bayesian theory, monte carlo method, mathematical models, calibration, uncertainty, decision support systems",
    author = "M.J.W. Jansen and T.H.J. Hagenaars",
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    Jansen, MJW & Hagenaars, THJ 2004, Calibration in a Bayesian modelling framework. in V Boekel, A Stein & V Bruggen (eds), Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain. Wageningen UR Frontis series, no. vol. 3, Dordrecht, pp. 47-55.

    Calibration in a Bayesian modelling framework. / Jansen, M.J.W.; Hagenaars, T.H.J.

    Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain. ed. / van Boekel; A. Stein; van Bruggen. Dordrecht, 2004. p. 47-55 (Wageningen UR Frontis series; No. vol. 3).

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

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    AU - Jansen, M.J.W.

    AU - Hagenaars, T.H.J.

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    AB - Bayesian statistics may constitute the core of a consistent and comprehensive framework for the statistical aspects of modelling complex processes that involve many parameters whose values are derived from many sources. Bayesian statistics holds great promises for model calibration, provides the perfect starting point for uncertainty analysis and provides an excellent starting point for decision support. The purpose of this paper is to draw attention to problems and possible solutions. It is not our intention to introduce ready-for-use methods

    KW - bayesiaanse theorie

    KW - monte carlo-methode

    KW - wiskundige modellen

    KW - kalibratie

    KW - onzekerheid

    KW - beslissingsondersteunende systemen

    KW - bayesian theory

    KW - monte carlo method

    KW - mathematical models

    KW - calibration

    KW - uncertainty

    KW - decision support systems

    M3 - Chapter

    SN - 1402019165

    T3 - Wageningen UR Frontis series

    SP - 47

    EP - 55

    BT - Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain

    A2 - Boekel, van

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    CY - Dordrecht

    ER -

    Jansen MJW, Hagenaars THJ. Calibration in a Bayesian modelling framework. In Boekel V, Stein A, Bruggen V, editors, Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain. Dordrecht. 2004. p. 47-55. (Wageningen UR Frontis series; vol. 3).