128 citations · 294 across the 8 of their papers we have counts for
8 papers
Bayesian analysis of finite population sampling in multivariate co-exchangeable structures with separable covariance matric
Simon C. Shaw, Michael Goldstein
We explore the effect of finite population sampling in design problems with many variables cross-classified in many ways. In particular, we investigate designs where we wish to sam…
Bayesian uncertainty analysis for complex systems biology models: emulation, global parameter searches and evaluation of gene functions
Ian Vernon, Junli Liu, Michael Goldstein +3
Background: Many mathematical models have now been employed across every area of systems biology. These models increasingly involve large numbers of unknown parameters, have comple…
Posterior Belief Assessment: Extracting Meaningful Subjective Judgements from Bayesian Analyses with Complex Statistical Models
Daniel Williamson, Michael Goldstein
In this paper, we are concerned with attributing meaning to the results of a Bayesian analysis for a problem which is sufficiently complex that we are unable to assert a precise co…
Galaxy Formation: Bayesian History Matching for the Observable Universe
Ian Vernon, Michael Goldstein, Richard Bower
Cosmologists at the Institute of Computational Cosmology, Durham University, have developed a state of the art model of galaxy formation known as Galform, intended to contribute to…
Bayes linear variance structure learning for inspection of large scale physical systems
David Randell, Michael Goldstein, Philip Jonathan
Modelling of inspection data for large scale physical systems is critical to assessment of their integrity. We present a general method for inference about system state and associa…
The Parameter Space of Galaxy Formation
R. G. Bower, I. Vernon, M. Goldstein +6
Semi-analytic models are a powerful tool for studying the formation of galaxies. However, these models inevitably involve a significant number of poorly constrained parameters that…