Andrew Golightly
Andrew Golightly
Associate Professor, Durham University
Verified email at - Homepage
Cited by
Cited by
Bayesian parameter inference for stochastic biochemical network models using particle Markov chain Monte Carlo
A Golightly, DJ Wilkinson
Interface Focus 1 (6), 807-820, 2011
Bayesian inference for stochastic kinetic models using a diffusion approximation
A Golightly, DJ Wilkinson
Biometrics 61 (3), 781-788, 2005
Bayesian inference for nonlinear multivariate diffusion models observed with error
A Golightly, DJ Wilkinson
Computational Statistics & Data Analysis 52 (3), 1674-1693, 2008
Bayesian sequential inference for nonlinear multivariate diffusions
A Golightly, DJ Wilkinson
Statistics and Computing 16, 323-338, 2006
Bayesian sequential inference for stochastic kinetic biochemical network models
A Golightly, DJ Wilkinson
Journal of Computational Biology 13 (3), 838-851, 2006
Delayed acceptance particle MCMC for exact inference in stochastic kinetic models
A Golightly, DA Henderson, C Sherlock
Statistics and Computing 25 (5), 1039-1055, 2015
Black-box variational inference for stochastic differential equations
T Ryder, A Golightly, AS McGough, D Prangle
International Conference on Machine Learning, 4423-4432, 2018
Adaptive, delayed-acceptance MCMC for targets with expensive likelihoods
C Sherlock, A Golightly, DA Henderson
Journal of Computational and Graphical Statistics 26 (2), 434-444, 2017
Improved bridge constructs for stochastic differential equations
GA Whitaker, A Golightly, RJ Boys, C Sherlock
Statistics and Computing 27, 885-900, 2017
Markov chain Monte Carlo algorithms for SDE parameter estimation
DJ Wilkinson, A Golightly
Learning and inference in computational systems biology, 253-275, 2010
Bayesian inference for Markov jump processes with informative observations
A Golightly, DJ Wilkinson
Statistical applications in genetics and molecular biology 14 (2), 169-188, 2015
Bayesian inference for generalized stochastic population growth models with application to aphids
CS Gillespie, A Golightly
Journal of the Royal Statistical Society: Series C (Applied Statistics) 59 …, 2010
Bayesian inference for diffusion-driven mixed-effects models
GA Whitaker, A Golightly, RJ Boys, C Sherlock
Simulation of stochastic kinetic models
A Golightly, CS Gillespie
In Silico Systems Biology, 169-187, 2013
Gross energy metabolism in mice under late onset, short term caloric restriction
KM Cameron, A Golightly, S Miwa, J Speakman, R Boys, T von Zglinicki
Mechanisms of ageing and development, 2011
Bayesian inference for hybrid discrete-continuous stochastic kinetic models
C Sherlock, A Golightly, CS Gillespie
Inverse Problems 30 (11), 114005, 2014
Bayesian inference for a wave-front model of the neolithization of Europe
AW Baggaley, GR Sarson, A Shukurov, RJ Boys, A Golightly
Physical Review E 86 (1), 016105, 2012
Ensemble MCMC: accelerating pseudo-marginal MCMC for state space models using the ensemble Kalman filter
C Drovandi, RG Everitt, A Golightly, D Prangle
Bayesian Analysis 17 (1), 223-260, 2022
Bayesian filtering for jump-diffusions with application to stochastic volatility
A Golightly
Journal of Computational and Graphical Statistics 18 (2), 384-400, 2009
Efficiency of delayed-acceptance random walk Metropolis algorithms
C Sherlock, AH Thiery, A Golightly
The Annals of Statistics 49 (5), 2972-2990, 2021
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