Eliciting multivariate uncertainty from experts: considerations and approaches along the expert judgement process

Abstract

In decision and risk analysis problems, modelling uncertainty probabilistically provides key insights and information for decision makers. A common challenge is that uncertainties are typically not isolated but interlinked which introduces complex (and often unexpected) effects on the model output. Therefore, dependence needs to be taken into account and modelled appropriately if simplifying assumptions, such as independence, are not sensible. Similar to the case of univariate uncertainty, which is described elsewhere in this book, relevant historical data to quantify a (dependence) model are often lacking or too costly to obtain. This may be true even when data on a model’s univariate quant..