| Bayesian design of experiments using approximate coordinate exchange AM Overstall, DC Woods Technometrics 59 (4), 458-470, 2017 | 111 | 2017 |
| Default Bayesian model determination methods for generalised linear mixed models AM Overstall, JJ Forster Computational Statistics & Data Analysis 54 (12), 3269-3288, 2010 | 53 | 2010 |
| Incomplete contingency tables with censored cells with application to estimating the number of people who inject drugs in Scotland AM Overstall, R King, SM Bird, SJ Hutchinson, G Hay Statistics in medicine 33 (9), 1564-1579, 2014 | 45 | 2014 |
| Bayesian design of experiments for generalized linear models and dimensional analysis with industrial and scientific application DC Woods, AM Overstall, M Adamou, TW Waite Quality Engineering 29 (1), 91-103, 2017 | 39 | 2017 |
| An approach for finding fully Bayesian optimal designs using normal-based approximations to loss functions AM Overstall, JM McGree, CC Drovandi Statistics and Computing 28, 343-358, 2018 | 38 | 2018 |
| Injecting drug users in Scotland, 2006: Listing, number, demography, and opiate-related death-rates R King, SM Bird, A Overstall, G Hay, SJ Hutchinson Addiction Research & Theory 21 (3), 235-246, 2013 | 38 | 2013 |
| Estimating prevalence of injecting drug users and associated heroin-related death rates in England by using regional data and incorporating prior information R King, SM Bird, AM Overstall, G Hay, SJ Hutchinson Journal of the Royal Statistical Society Series A: Statistics in Society 177 …, 2014 | 35 | 2014 |
| Multivariate emulation of computer simulators: model selection and diagnostics with application to a humanitarian relief model AM Overstall, DC Woods Journal of the Royal Statistical Society Series C: Applied Statistics 65 (4 …, 2016 | 33 | 2016 |
| conting: An R package for Bayesian analysis of complete and incomplete contingency tables A Overstall, R King Journal of Statistical Software 58 (7), 1-27, 2014 | 33 | 2014 |
| Reversible jump methods for generalised linear models and generalised linear mixed models JJ Forster, RC Gill, AM Overstall Statistics and Computing 22, 107-120, 2012 | 32 | 2012 |
| acebayes: An R package for Bayesian optimal design of experiments via approximate coordinate exchange A Overstall, D Woods, M Adamou arXiv preprint arXiv:1705.08096, 2017 | 27 | 2017 |
| Quantifying uncertainty in transdimensional Markov chain Monte Carlo using discrete Markov models DW Heck, AM Overstall, QF Gronau, EJ Wagenmakers Statistics and Computing 29, 631-643, 2019 | 24 | 2019 |
| Bayesian optimal design for ordinary differential equation models with application in biological science AM Overstall, DC Woods, BM Parker Journal of the American Statistical Association, 2019 | 22 | 2019 |
| Bayesian design of experiments for intractable likelihood models using coupled auxiliary models and multivariate emulation A Overstall, J McGree | 19 | 2020 |
| Bayesian prediction for physical models with application to the optimization of the synthesis of pharmaceutical products using chemical kinetics AM Overstall, DC Woods, KJ Martin Computational Statistics & Data Analysis 132, 126-142, 2019 | 18 | 2019 |
| A strategy for Bayesian inference for computationally expensive models with application to the estimation of stem cell properties AM Overstall, DC Woods Biometrics 69 (2), 458-468, 2013 | 14 | 2013 |
| A default prior distribution for contingency tables with dependent factor levels AM Overstall, R King Statistical Methodology 16, 90-99, 2014 | 12 | 2014 |
| Bayesian adaptive N‐of‐1 trials for estimating population and individual treatment effects SGJ Senarathne, AM Overstall, JM McGree Statistics in Medicine 39 (29), 4499-4518, 2020 | 10 | 2020 |
| Bayesian decision-theoretic design of experiments under an alternative model A Overstall, J McGree Bayesian Analysis 17 (4), 1021-1041, 2022 | 6 | 2022 |
| Population size estimation and capture–recapture methods R King, A Overstall | | 2015 |
