Christopher Drovandi

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Anthony PettittEmeritus Professor of Statistics, Queensland University of TechnologyVerified email at qut.edu.au
Kerrie MengersenQueensland University of TechnologyVerified email at qut.edu.au
James McGreeQueensland University of TechnologyVerified email at qut.edu.au
David NottAssociate Professor of Statistics, National University of SingaporeVerified email at nus.edu.sg
David Tyler FrazierMonash University, Department of Econometrics and Business StatisticsVerified email at monash.edu
Elizabeth RyanMonash UniversityVerified email at monash.edu
Leah SouthQueensland University of TechnologyVerified email at qut.edu.au
Brodie A. J. LawsonQUT Centre for Data Science, ARC Centre of Excellence for Plant Success in Nature and AgricultureVerified email at qut.edu.au
kevin burrageProfessor Computational Mathematics, Queensland University of TechnologyVerified email at qut.edu.au
Anthony LeeSchool of Mathematics, University of BristolVerified email at bristol.ac.uk
Antonietta MiraProfessore di Statistica, Università della Svizzera italiana, LuganoVerified email at usi.ch
David WarneLecturer in Statistical Data Science, Queensland University of TechnologyVerified email at qut.edu.au
Matthew J SimpsonQueensland University of TechnologyVerified email at qut.edu.au
robert kohnProfessor of Economics University of New South WalesVerified email at unsw.edu.au
Scott SissonProfessor of Statistics & Data Science, University of New South WalesVerified email at unsw.edu.au
pamela burrageQueensland University of TechnologyVerified email at qut.edu.au
Blanca RodriguezUniversity of OxfordVerified email at cs.ox.ac.uk
Ian B. StewartProfessor of Exercise Physiology, Queensland University of TechnologyVerified email at qut.edu.au
Robert SalomoneQueensland University of TechnologyVerified email at qut.edu.au
M. Julian CaleyVerified email at qut.edu.au

Christopher Drovandi

Professor of Statistics, Queensland University of Technology

Verified email at qut.edu.au - Homepage

Bayesian Computation Likelihood-free Methods Bayesian Experimental Design Applications of Bayesian Statistics


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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	332	2016
Estimation of parameters for macroparasite population evolution using approximate Bayesian computation CC Drovandi, AN Pettitt Biometrics 67 (1), 225-233, 2011	272	2011
Bayesian synthetic likelihood LF Price, CC Drovandi, A Lee, DJ Nott Journal of Computational and Graphical Statistics 27 (1), 1-11, 2018	236	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	175	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	128	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	118	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	106	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	94	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	75	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	71	2013
Variational Bayes with synthetic likelihood VMH Ong, DJ Nott, MN Tran, SA Sisson, CC Drovandi Statistics and Computing 28, 971-988, 2018	69	2018
Bayesian experimental design for models with intractable likelihoods CC Drovandi, AN Pettitt Biometrics 69 (4), 937-948, 2013	68	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	66	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	60	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	60	2014
Fully Bayesian experimental design for pharmacokinetic studies EG Ryan, CC Drovandi, AN Pettitt Entropy 17 (3), 1063-1089, 2015	54	2015
Robust approximate Bayesian inference with synthetic likelihood DT Frazier, C Drovandi Journal of Computational and Graphical Statistics 30 (4), 958-976, 2021	51	2021
Robust Bayesian synthetic likelihood via a semi-parametric approach Z An, DJ Nott, C Drovandi Statistics and Computing 30 (3), 543-557, 2020	51	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	47	2023

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