25 citations · 83 across the 14 of their papers we have counts for
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Bayesian design of experiments for generalised linear models and dimensional analysis with industrial and scientific application
David C. Woods, Antony M. Overstall, Maria Adamou +1
The design of an experiment can be always be considered at least implicitly Bayesian, with prior knowledge used informally to aid decisions such as the variables to be studied and…
Bayesian prediction for physical models with application to the optimization of the synthesis of pharmaceutical products using chemical kinetics
Antony Overstall, David Woods, Kieran Martin
Quality control in industrial processes is increasingly making use of prior scientific knowledge, often encoded in physical models that require numerical approximation. Statistical…
Model selection via Bayesian information capacity designs for generalised linear models
David C. Woods, James M. McGree, Susan M. Lewis
The first investigation is made of designs for screening experiments where the response variable is approximated by a generalised linear model. A Bayesian information capacity crit…