A mixture of experts model for rank data with applications in election studies IC Gormley, TB Murphy Annals of Applied Statistics 2 (4), 1452-1477, 2008 | 116 | 2008 |
Probabilistic principal component analysis for metabolomic data G Nyamundanda, L Brennan, IC Gormley BMC bioinformatics 11 (1), 1-11, 2010 | 112 | 2010 |
Exploring voting blocs within the Irish electorate: A mixture modeling approach IC Gormley, TB Murphy Journal of the American Statistical Association 103 (483), 1014-1027, 2008 | 96 | 2008 |
Analysis of Irish third‐level college applications data IC Gormley, TB Murphy Journal of the Royal Statistical Society: Series A (Statistics in Society …, 2006 | 75 | 2006 |
A latent space model for rank data IC Gormley, TB Murphy ICML Workshop on Statistical Network Analysis, 90-102, 2006 | 67 | 2006 |
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 | 65 | 2016 |
MetSizeR: selecting the optimal sample size for metabolomic studies using an analysis based approach G Nyamundanda, IC Gormley, Y Fan, WM Gallagher, L Brennan BMC bioinformatics 14 (1), 1-8, 2013 | 62 | 2013 |
Model based clustering for mixed data: clustMD D McParland, IC Gormley Advances in Data Analysis and Classification 10 (2), 155-169, 2016 | 51 | 2016 |
A grade of membership model for rank data IC Gormley, TB Murphy Bayesian Analysis 4 (2), 265-295, 2009 | 51 | 2009 |
Transcriptomic coordination in the human metabolic network reveals links between n-3 fat intake, adipose tissue gene expression and metabolic health MJ Morine, AC Tierney, B Van Ommen, H Daniel, S Toomey, IMF Gjelstad, ... PLoS comput biol 7 (11), e1002223, 2011 | 37 | 2011 |
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 | 33 | 2012 |
A mixture of experts latent position cluster model for social network data IC Gormley, TB Murphy Statistical methodology 7 (3), 385-405, 2010 | 33 | 2010 |
Influence of weather variables on pain severity in end-stage osteoarthritis SA Brennan, T Harney, JM Queally, JOC McGoona, IC Gormley, ... International orthopaedics 36 (3), 643-646, 2012 | 31 | 2012 |
Dislocation of primary total hip arthroplasty and the risk of redislocation SA Brennan, F Khan, C Kiernan, JM Queally, J McQuillan, IC Gormley, ... Hip International 22 (5), 500-504, 2012 | 30 | 2012 |
Clustering South African households based on their asset status using latent variable models D McParland, IC Gormley, TH McCormick, SJ Clark, CW Kabudula, ... The annals of applied statistics 8 (2), 747, 2014 | 27 | 2014 |
Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome MJ Morine, J McMonagle, S Toomey, CM Reynolds, AP Moloney, ... BMC bioinformatics 11 (1), 1-12, 2010 | 23 | 2010 |
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 | 21* | 2019 |
A dynamic probabilistic principal components model for the analysis of longitudinal metabolomics data G Nyamundanda, IC Gormley, L Brennan Journal of the Royal Statistical Society: Series C: Applied Statistics, 763-782, 2014 | 21 | 2014 |
Clustering ordinal data via latent variable models D McParland, IC Gormley Algorithms from and for Nature and Life, 127-135, 2013 | 17 | 2013 |
Infinite mixtures of infinite factor analysers K Murphy, C Viroli, IC Gormley Bayesian Analysis, 2020 | 16 | 2020 |