Expert judgement for dependence in probabilistic modelling : a systematic literature review and future research directions
Werner, Christoph and Bedford, Tim and Cooke, Roger M. and Hanea, Anca M. and Morales-Napoles, Oswaldo (2016) Expert judgement for dependence in probabilistic modelling : a systematic literature review and future research directions. European Journal of Operational Research, 258 (3). pp. 801-819. ISSN 0377-2217 (https://doi.org/10.1016/j.ejor.2016.10.018)
Preview |
Text.
Filename: Werner_etal_EJOR_2016_Expert_judgement_for_dependence_in_probabilistic.pdf
Accepted Author Manuscript License: Download (697kB)| Preview |
Abstract
Many applications in decision making under uncertainty and probabilistic risk assessment require the assessment of mul- tiple, dependent uncertain quantities, so that in addition to marginal distributions, interdependence needs to be modelled in order to properly understand the overall risk. Nevertheless, relevant historical data on dependence information are often not available or simply too costly to obtain. In this case, the only sensible option is to elicit this uncertainty through the use of expert judgements. In expert judgement studies, a structured approach to eliciting variables of interest is desirable so that their assessment is methodologically robust. One of the key decisions during the elicitation process is the form in which the uncertainties are elicited. This choice is subject to various, potentially con icting, desiderata related to e.g. modelling convenience, coherence between elicitation parameters and the model, combining judgements, and the assessment burden for the experts. While extensive and systematic guidance to address these considerations exists for single variable uncertainty elicitation, for higher dimensions very little such guidance is available. Therefore this paper o ers a systematic review of the current literature on eliciting dependence. The literature on the elicitation of dependence parameters such as correlations is presented alongside commonly used dependence models and experience from case studies. From this, guidance about the strategy for dependence assessment is given and gaps in the existing research are identi ed to determine future directions for structured methods to elicit dependence.
ORCID iDs
Werner, Christoph ORCID: https://orcid.org/0000-0002-5307-9686, Bedford, Tim ORCID: https://orcid.org/0000-0002-3545-2088, Cooke, Roger M., Hanea, Anca M. and Morales-Napoles, Oswaldo;-
-
Item type: Article ID code: 58428 Dates: DateEvent22 October 2016Published9 October 2016AcceptedSubjects: Social Sciences > Industries. Land use. Labor > Management. Industrial Management Department: Strathclyde Business School > Management Science Depositing user: Pure Administrator Date deposited: 02 Nov 2016 09:31 Last modified: 21 Nov 2024 01:12 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/58428