| Clustering with the multivariate normal inverse Gaussian distribution A O’Hagan, TB Murphy, IC Gormley, PD McNicholas, D Karlis Computational Statistics & Data Analysis 93, 18-30, 2016 | 54 | 2016 |
| Computational aspects of fitting mixture models via the expectation–maximization algorithm A O’Hagan, TB Murphy, IC Gormley Computational Statistics & Data Analysis 56 (12), 3843-3864, 2012 | 31 | 2012 |
| Investigation of parameter uncertainty in clustering using a Gaussian mixture model via jackknife, bootstrap and weighted likelihood bootstrap A O’Hagan, TB Murphy, L Scrucca, IC Gormley Computational Statistics 34 (4), 1779-1813, 2019 | 14* | 2019 |
| Improved model-based clustering performance using Bayesian initialization averaging A O’Hagan, A White Computational Statistics 34 (1), 201-231, 2019 | 5 | 2019 |
| Model-Based and Nonparametric Approaches to Clustering for Data Compression in Actuarial Applications A O’Hagan, C Ferrari North American Actuarial Journal 21 (1), 107-146, 2017 | 3 | 2017 |
| Motor insurance claim modelling with factor collapsing and Bayesian model averaging S Hu, A O'Hagan, TB Murphy Stat 7 (1), e180, 2018 | 2 | 2018 |
| Actuarial Risk Matrices: The Nearest Positive Semidefinite Matrix Problem S Cutajar, H Smigoc, A O’Hagan North American Actuarial Journal 21 (4), 552-564, 2017 | 2 | 2017 |
| Can’t Buy Me Love? Specific and Diffuse Reciprocity in International Relations S Brazys, A O’Hagan, D Pankeπ, O Westerwinterφ | 2 | 2017 |
| Topics in model-based clustering and classification A O'Hagan University College Dublin, 2012 | 2 | 2012 |
