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Record number 404158
Title Calibration in a Bayesian modelling framework
Author(s) Jansen, M.J.W.; Hagenaars, T.H.J.
Source In: Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain / Boekel, van, Stein, A., Bruggen, van, Dordrecht : Kluwer (Wageningen UR Frontis series vol. 3) - ISBN 1402019165 - p. 47 - 55.
Department(s) PRI Biometris
Publication type Peer reviewed book chapter
Publication year 2004
Keyword(s) bayesiaanse theorie - monte carlo-methode - wiskundige modellen - kalibratie - onzekerheid - beslissingsondersteunende systemen - bayesian theory - monte carlo method - mathematical models - calibration - uncertainty - decision support systems
Categories Mathematical Statistics
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
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