 Probabilistic inversion for chicken processing linesRoger Cooke, Maarten Nauta, Arie H. Havelaar and Ine van der Fels Reliability Engineering and System Safety, 2006, vol. 91, issue 10, 1364-1372 Abstract: We discuss an application of probabilistic inversion techniques to a model of campylobacter transmission in chicken processing lines. Such techniques are indicated when we wish to quantify a model which is new and perhaps unfamiliar to the expert community. In this case there are no measurements for estimating model parameters, and experts are typically unable to give a considered judgment. In such cases, experts are asked to quantify their uncertainty regarding variables which can be predicted by the model. The experts’ distributions (after combination) are then pulled back onto the parameter space of the model, a process termed “probabilistic inversion†. This study illustrates two such techniques, iterative proportional fitting (IPF) and PARmeter fitting for uncertain models (PARFUM). In addition, we illustrate how expert judgement on predicted observable quantities in combination with probabilistic inversion may be used for model validation and/or model criticism. Keywords: Probabilistic inversion; IPF; PARFUM; Campylobacter; Transport models; Expert judgment; Entropy; Information (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:91:y:2006:i:10:p:1364-1372 DOI: 10.1016/j.ress.2005.11.054 Access Statistics for this article Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares More articles in Reliability Engineering and System Safety from Elsevier |
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