Browsing by Author "Bedford, Tim"

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    Approximate uncertainty modeling in risk analysis with vine copulas
    (Wiley, 2015-09-02) Bedford, Tim; Daneshkhah, Alireza; Wilson, Kevin J.
    Many applications of risk analysis require us to jointly model multiple uncertain quantities. Bayesian networks and copulas are two common approaches to modeling joint uncertainties with probability distributions. This article focuses on new methodologies for copulas by developing work of Cooke, Bedford, Kurowica, and others on vines as a way of constructing higher dimensional distributions that do not suffer from some of the restrictions of alternatives such as the multivariate Gaussian copula. The article provides a fundamental approximation result, demonstrating that we can approximate any density as closely as we like using vines. It further operationalizes this result by showing how minimum information copulas can be used to provide parametric classes of copulas that have such good levels of approximation. We extend previous approaches using vines by considering nonconstant conditional dependencies, which are particularly relevant in financial risk modeling. We discuss how such models may be quantified, in terms of expert judgment or by fitting data, and illustrate the approach by modeling two financial data sets.
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    Assessing parameter uncertainty on coupled models using minimum information methods
    (Elsevier Science B.V., Amsterdam., 2014-05-31T00:00:00Z) Bedford, Tim; Wilson, Kevin J.; Daneshkhah, Alireza
    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.
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    Human reliability analysis: A critique and review for managers
    (Elsevier Science B.V., Amsterdam., 2011-07-01T00:00:00Z) French, Simon; Bedford, Tim; Pollard, Simon J. T.; Soane, Emma
    In running our increasingly complex business systems, formal risk analyses and risk management techniques are becoming a more important part of a manager's tool-kit. Moreover, it is also becoming apparent that human behaviour is often a root or significant contributing cause of system failure. This latter observation is not novel; for more than 30 years it has been recognised that the role of human operations in safety critical systems is so important that they should be explicitly modelled as part of the risk assessment of plant operations. This has led to the development of a range of methods under the general heading of human reliability analysis (HRA) to account for the effects of human error in risk and reliability analysis. The modelling approaches used in HRA, however, tend to be focussed on easily describable sequential, generally low-level tasks, which are not the main source of systemic errors. Moreover, they focus on errors rather than the effects of all forms of human behaviour. In this paper we review and discuss HRA methodologies, arguing that there is a need for considerable further research and development before they meet the needs of modern risk and reliability analyses and are able to provide managers with the guidance they need to manage complex systems safely. We provide some suggestions for how work in this area should develop.
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    A role for human reliability analysis (HRA) in preventing drinking water incidents and securing safe drinking water
    (Elsevier Science B.V., Amsterdam., 2009-05-05T00:00:00Z) Wu, Shaomin; Hrudey, Steve E.; French, Simon; Bedford, Tim; Soane, Emma; Pollard, Simon J. T.
    The prevalence of water quality incidents and disease outbreaks suggests an imperative to analyse and understand the roles of operators and organisations in the water supply system. One means considered in this paper is through human reliability analysis (HRA). We classify the human errors contributing to 62 drinking water accidents occurring in affluent countries from 1974 to 2001; define the lifecycle of these incidents; and adapt Reason's ‘Swiss cheese’ model for drinking water safety. We discuss the role of HRA in human error reduction and drinking water safety and propose a future research agenda for human error reduction in the water sec