| Prediction of Staphylococcus aureus antimicrobial resistance by whole-genome sequencing NC Gordon, JR Price, K Cole, R Everitt, M Morgan, J Finney, AM Kearns, ... Journal of Clinical Microbiology 52 (4), 1182-1191, 2014 | 382 | 2014 |
| Evolutionary dynamics of Staphylococcus aureus during progression from carriage to disease BC Young, T Golubchik, EM Batty, R Fung, H Larner-Svensson, ... Proceedings of the National Academy of Sciences 109 (12), 4550-4555, 2012 | 318 | 2012 |
| Within-host evolution of Staphylococcus aureus during asymptomatic carriage T Golubchik, EM Batty, RR Miller, H Farr, BC Young, H Larner-Svensson, ... PloS one 8 (5), e61319, 2013 | 230 | 2013 |
| Noisy Monte Carlo: Convergence of Markov chains with approximate transition kernels P Alquier, N Friel, R Everitt, A Boland Statistics and Computing 26 (1), 29-47, 2016 | 168 | 2016 |
| Mobile elements drive recombination hotspots in the core genome of Staphylococcus aureus RG Everitt, X Didelot, EM Batty, RR Miller, K Knox, BC Young, R Bowden, ... Nature Communications 5, 2014 | 161* | 2014 |
| Likelihood-free estimation of model evidence X Didelot, RG Everitt, AM Johansen, DJ Lawson Bayesian Analysis 6 (1), 49-76, 2011 | 154 | 2011 |
| Bayesian Parameter Estimation for Latent Markov Random Fields and Social Networks RG Everitt Journal of Computational and Graphical Statistics 21 (4), 940-960, 2012 | 114 | 2012 |
| Predicting global patterns of long-term climate change from short-term simulations using machine learning LA Mansfield, PJ Nowack, M Kasoar, RG Everitt, WJ Collins, ... npj Climate and Atmospheric Science 3 (1), 44, 2020 | 57 | 2020 |
| Multi-target out-of-sequence data association: Tracking using graphical models SR Maskell, RG Everitt, R Wright, M Briers Information Fusion 7 (4), 434-447, 2006 | 54 | 2006 |
| Bayesian model comparison with un-normalised likelihoods RG Everitt, AM Johansen, E Rowing, M Evdemon-Hogan Statistics and Computing 27, 403-422, 2017 | 41* | 2017 |
| A rare event approach to high-dimensional approximate Bayesian computation D Prangle, RG Everitt, T Kypraios Statistics and Computing 28 (4), 819–834, 2018 | 33 | 2018 |
| Sequential Monte Carlo with transformations RG Everitt, R Culliford, F Medina-Aguayo, DJ Wilson Statistics and Computing 30, 663-676, 2020 | 22* | 2020 |
| 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 | 20 | 2022 |
| Delayed acceptance ABC-SMC RG Everitt, PA Rowińska Journal of Computational and Graphical Statistics 30 (1), 55-66, 2021 | 14 | 2021 |
| Bootstrapped synthetic likelihood RG Everitt arXiv preprint arXiv:1711.05825, 2017 | 14 | 2017 |
| Hypothesis management in situation assessment RG Everitt, AD Marrs Proceedings of IEEE Aerospace Conference, 1895-1903, 2003 | 8 | 2003 |
| Incorporating environmental variability in a spatially-explicit individual-based model of European sea bass JW Watson, R Boyd, R Dutta, G Vasdekis, ND Walker, S Roy, R Everitt, ... Ecological Modelling 466, 109878, 2022 | 7 | 2022 |
| Online Bayesian Inference in Some Time-Frequency Representations of Non-Stationary Processes RG Everitt, C Andrieu, M Davy IEEE Transactions on Signal Processing 61 (22), 5755-5766, 2013 | 7 | 2013 |
| Marginal sequential Monte Carlo for doubly intractable models RG Everitt, D Prangle, P Maybank, M Bell arXiv preprint arXiv:1710.04382, 2017 | 6 | 2017 |
| Fast approximate Bayesian inference for stable differential equation models P Maybank, I Bojak, RG Everitt arXiv preprint arXiv:1706.00689, 2017 | 5 | 2017 |
Daniel J WilsonUniversity of Oxford在 bdi.ox.ac.uk 的电子邮件经过验证
