The Bayesian approach to quantifying, analysing and reducing uncertainty in the application
of complex process models is attracting increasing attention amongst users of such models …

Experiments have long been used to study the relationship between a set of inputs to a
physical system and the resulting output. Termed physical experiments in this text, there is a …

Heavy atomic nuclei have an excess of neutrons over protons, which leads to the formation
of a neutron skin whose thickness is sensitive to details of the nuclear force. This links …

In many areas of science and technology, mathematical models are built to simulate
complex real world phenomena. Such models are typically implemented in large computer …

Modern data and computational resources, coupled with algorithmic and theoretical
advances to exploit these, allow disease dynamic models to be parameterised with …

We present a framework that enables computer model evaluation oriented toward
answering the question: Does the computer model adequately represent reality? The …

Having the ability to work with complex models can be highly beneficial. However, complex
models often have intractable likelihoods, so methods that involve evaluation of the …

In many scientific disciplines complex computer models are used to understand the
behaviour of large scale physical systems. An uncertainty analysis of such a computer …

A key question in evaluation of computer models is Does the computer model adequately
represent reality? A six-step process for computer model validation is set out in Bayarri et …

Bayesian methods combine information available from data with any prior information
available from expert knowledge. The Bayes linear approach follows this path, offering a …