Calibration in a Bayesian modelling framwork

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

    Research output: Chapter in Book/Report/Conference proceedingConference paper

    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 publicationProceedings of the Frontis Workshop on Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain, Wageningen, The Netherlands, 01-14 May 2003
    EditorsM.A.J.S. Boekel, A. Stein, A.H.C. van Bruggen
    Place of PublicationDordrecht
    PublisherKluwer Academic Publishers
    Pages47-55
    ISBN (Print)9781402019173
    Publication statusPublished - 2004
    EventFrontis Workshop on Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain -
    Duration: 1 May 200314 May 2003

    Workshop

    WorkshopFrontis Workshop on Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain
    Period1/05/0314/05/03

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    Cite this

    Jansen, M. J. W., & Hagenaars, T. H. J. (2004). Calibration in a Bayesian modelling framwork. In M. A. J. S. Boekel, A. Stein, & A. H. C. V. Bruggen (Eds.), Proceedings of the Frontis Workshop on Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain, Wageningen, The Netherlands, 01-14 May 2003 (pp. 47-55). Dordrecht: Kluwer Academic Publishers.