A review of modern computational algorithms for Bayesian optimal design EG Ryan, CC Drovandi, JM McGree, AN Pettitt International Statistical Review 84 (1), 128-154, 2016 | 314 | 2016 |
Estimation of parameters for macroparasite population evolution using approximate Bayesian computation CC Drovandi, AN Pettitt Biometrics 67 (1), 225-233, 2011 | 267 | 2011 |
Bayesian synthetic likelihood LF Price, CC Drovandi, A Lee, DJ Nott Journal of Computational and Graphical Statistics 27 (1), 1-11, 2018 | 228 | 2018 |
Water quality mediates resilience on the Great Barrier Reef MA MacNeil, C Mellin, S Matthews, NH Wolff, TR McClanahan, M Devlin, ... Nature Ecology & Evolution 3 (4), 620-627, 2019 | 169 | 2019 |
Approximate Bayesian computation using indirect inference CC Drovandi, AN Pettitt, MJ Faddy Journal of the Royal Statistical Society Series C: Applied Statistics 60 (3 …, 2011 | 127 | 2011 |
Likelihood-free Bayesian estimation of multivariate quantile distributions CC Drovandi, AN Pettitt Computational Statistics & Data Analysis 55 (9), 2541-2556, 2011 | 126 | 2011 |
Bayesian Indirect Inference using a Parametric Auxiliary Model CC Drovandi, AN Pettitt, A Lee Statistical Science 30 (1), 72-95, 2015 | 115 | 2015 |
A sequential Monte Carlo algorithm to incorporate model uncertainty in Bayesian sequential design CC Drovandi, JM McGree, AN Pettitt Journal of Computational and Graphical Statistics 23 (1), 3-24, 2014 | 102 | 2014 |
Bayesian estimation of small effects in exercise and sports science KL Mengersen, CC Drovandi, CP Robert, DB Pyne, CJ Gore PloS one 11 (4), e0147311, 2016 | 93 | 2016 |
Unlocking data sets by calibrating populations of models to data density: A study in atrial electrophysiology BAJ Lawson, CC Drovandi, N Cusimano, P Burrage, B Rodriguez, ... Science advances 4 (1), e1701676, 2018 | 74 | 2018 |
Variational Bayes with synthetic likelihood VMH Ong, DJ Nott, MN Tran, SA Sisson, CC Drovandi Statistics and Computing 28, 971-988, 2018 | 70 | 2018 |
Sequential Monte Carlo for Bayesian sequentially designed experiments for discrete data CC Drovandi, JM McGree, AN Pettitt Computational Statistics & Data Analysis 57 (1), 320-335, 2013 | 69 | 2013 |
Bayesian experimental design for models with intractable likelihoods CC Drovandi, AN Pettitt Biometrics 69 (4), 937-948, 2013 | 67 | 2013 |
Principles of experimental design for Big Data analysis CC Drovandi, C Holmes, JM McGree, K Mengersen, S Richardson, ... Statistical science: a review journal of the Institute of Mathematical …, 2017 | 62 | 2017 |
Quantifying uncertainty in parameter estimates for stochastic models of collective cell spreading using approximate Bayesian computation BN Vo, CC Drovandi, AN Pettitt, MJ Simpson Mathematical biosciences 263, 133-142, 2015 | 59 | 2015 |
Towards Bayesian experimental design for nonlinear models that require a large number of sampling times EG Ryan, CC Drovandi, MH Thompson, AN Pettitt Computational Statistics & Data Analysis 70, 45-60, 2014 | 58 | 2014 |
Fully Bayesian experimental design for pharmacokinetic studies EG Ryan, CC Drovandi, AN Pettitt Entropy 17 (3), 1063-1089, 2015 | 53 | 2015 |
Robust approximate Bayesian inference with synthetic likelihood DT Frazier, C Drovandi Journal of Computational and Graphical Statistics 30 (4), 958-976, 2021 | 49 | 2021 |
Robust Bayesian synthetic likelihood via a semi-parametric approach Z An, DJ Nott, C Drovandi Statistics and Computing 30 (3), 543-557, 2020 | 49 | 2020 |
Bayesian inference using synthetic likelihood: asymptotics and adjustments DT Frazier, DJ Nott, C Drovandi, R Kohn Journal of the American Statistical Association 118 (544), 2821-2832, 2023 | 43 | 2023 |