Assessing parameter uncertainty on coupled models using minimum information methods
| dc.contributor.author | Bedford, Tim | - |
| dc.contributor.author | Wilson, Kevin J. | - |
| dc.contributor.author | Daneshkhah, Alireza | - |
| dc.date.accessioned | 2014-07-11T04:01:01Z | |
| dc.date.available | 2014-07-11T04:01:01Z | |
| dc.date.issued | 2014-05-31T00:00:00Z | - |
| dc.description.abstract | Probabilistic inversion is used to take expert uncertainty assessments about observable model outputs and build from them a distribution on the model parameters that captures the uncertainty expressed by the experts. In this paper we look at ways to use minimum information methods to do this, focussing in particular on the problem of ensuring consistency between expert assessments about differing variables, either as outputs from a single model, or potentially as outputs along a chain of models. The paper shows how such a problem can be structured and then illustrates the method with two examples; one involving failure rates of equipment in series systems and the other atmospheric dispersion and deposition. | en_UK |
| dc.identifier.citation | Tim Bedford, Kevin J. Wilson, Alireza Daneshkhah, Assessing parameter uncertainty on coupled models using minimum information methods, Reliability Engineering & System Safety, Volume 125, May 2014, Pages 3–12. | |
| dc.identifier.issn | 0951-8320 | - |
| dc.identifier.uri | http://dx.doi.org/10.1016/j.ress.2013.05.011 | - |
| dc.identifier.uri | http://dspace.lib.cranfield.ac.uk/handle/1826/8613 | |
| dc.language.iso | en_UK | - |
| dc.publisher | Elsevier Science B.V., Amsterdam. | en_UK |
| dc.rights | NOTICE: this is the author’s version of a work that was accepted for publication in Reliability Engineering & System Safety. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Reliability Engineering & System Safety, VOL 125, (2014) DOI: 10.1016/j.ress.2013.05.011 | |
| dc.title | Assessing parameter uncertainty on coupled models using minimum information methods | en_UK |
| dc.type | Article | - |