Christopher Drovandi
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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
Estimation of parameters for macroparasite population evolution using approximate Bayesian computation
CC Drovandi, AN Pettitt
Biometrics 67 (1), 225-233, 2011
Bayesian synthetic likelihood
LF Price, CC Drovandi, A Lee, DJ Nott
Journal of Computational and Graphical Statistics 27 (1), 1-11, 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
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
Likelihood-free Bayesian estimation of multivariate quantile distributions
CC Drovandi, AN Pettitt
Computational Statistics & Data Analysis 55 (9), 2541-2556, 2011
Bayesian Indirect Inference using a Parametric Auxiliary Model
CC Drovandi, AN Pettitt, A Lee
Statistical Science 30 (1), 72-95, 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
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
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
Variational Bayes with synthetic likelihood
VMH Ong, DJ Nott, MN Tran, SA Sisson, CC Drovandi
Statistics and Computing 28, 971-988, 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
Bayesian experimental design for models with intractable likelihoods
CC Drovandi, AN Pettitt
Biometrics 69 (4), 937-948, 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
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
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
Fully Bayesian experimental design for pharmacokinetic studies
EG Ryan, CC Drovandi, AN Pettitt
Entropy 17 (3), 1063-1089, 2015
Robust approximate Bayesian inference with synthetic likelihood
DT Frazier, C Drovandi
Journal of Computational and Graphical Statistics 30 (4), 958-976, 2021
Robust Bayesian synthetic likelihood via a semi-parametric approach
Z An, DJ Nott, C Drovandi
Statistics and Computing 30 (3), 543-557, 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
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