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A web-based tool for eliciting probability distributions from experts

Morris, David E.; Oakley, Jeremy E.; Crowe, John A.

Authors

DAVID MORRIS DAVID.MORRIS@NOTTINGHAM.AC.UK
Assistant Professor in Electronicengineering

Jeremy E. Oakley

John A. Crowe John.Crowe@nottingham.ac.uk



Abstract

We present a web-based probability distribution elicitation tool: The MATCH Uncertainty Elicitation Tool. The Tool is designed to help elicit probability distributions about uncertain model parameters from experts, in situations where suitable data is either unavailable or sparse. The Tool is free to use, and offers five different techniques for eliciting univariate probability distributions. A key feature of the Tool is that users can log in from different sites and view and interact with the same graphical displays, so that expert elicitation sessions can be conducted remotely (in conjunction with tele- or videoconferencing). This will make probability elicitation easier in situations where it is difficult to interview experts in person. Even when conducting elicitation remotely, interviewers will be able to follow good elicitation practice, advise the experts, and provide instantaneous feedback and assistance. © 2013 The Authors.

Citation

Morris, D. E., Oakley, J. E., & Crowe, J. A. (2014). A web-based tool for eliciting probability distributions from experts. Environmental Modelling and Software, 52, 1-4. https://doi.org/10.1016/j.envsoft.2013.10.010

Journal Article Type Article
Acceptance Date Oct 13, 2013
Online Publication Date Oct 12, 2013
Publication Date 2014-02
Deposit Date Jul 14, 2016
Publicly Available Date Jul 14, 2016
Journal Environmental Modelling & Software
Print ISSN 1364-8152
Electronic ISSN 1873-6726
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 52
Pages 1-4
DOI https://doi.org/10.1016/j.envsoft.2013.10.010
Keywords Bayesian prior distribution; Expert judgement; Subjective probability; Web-based elicitation
Public URL http://eprints.nottingham.ac.uk/id/eprint/35002
Publisher URL http://www.sciencedirect.com/science/article/pii/S1364815213002533
Copyright Statement Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0

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Publisher Licence URL
http://creativecommons.org/licenses/by/3.0/





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