| mclust 5: Clustering, Classification and Density Estimation Using Gaussian Finite Mixture Models L Scrucca, M Fop, TB Murphy, AE Raftery The R Journal 8 (1), 289-317, 2016 | 3407 | 2016 |
| mclust Version 4 for R: Normal Mixture Modeling for Model-Based Clustering, Classification, and Density Estimation C Fraley, AE Raftery, TB Murphy, L Scrucca https://www.stat.washington.edu/research/reports/2012/tr597.pdf, 2012 | 1311 | 2012 |
| Parsimonious Gaussian mixture models PD Mcnicholas, TB Murphy Statistics and Computing 18 (3), 285-296, 2008 | 412 | 2008 |
| Model-based clustering and classification for data science: with applications in R C Bouveyron, G Celeux, TB Murphy, AE Raftery Cambridge University Press, 2019 | 406 | 2019 |
| Desulfovibrio bacterial species are increased in ulcerative colitis F Rowan, NG Docherty, M Murphy, B Murphy, JC Coffey, PR O‘Connell Diseases of the Colon & Rectum 53 (11), 1530, 2010 | 363 | 2010 |
| Model-based clustering, classification, and density estimation using mclust in R L Scrucca, C Fraley, TB Murphy, AE Raftery Chapman and Hall/CRC, 2023 | 355 | 2023 |
| Model-based clustering of microarray expression data via latent Gaussian mixture models PD McNicholas, TB Murphy Bioinformatics 26 (21), 2705, 2010 | 250 | 2010 |
| Novel glycan biomarkers for the detection of lung cancer JN Arnold, R Saldova, MC Galligan, TB Murphy, Y Mimura-Kimura, ... Journal of Proteome Research, 2011 | 232 | 2011 |
| Serial and parallel implementations of model-based clustering via parsimonious Gaussian mixture models PD McNicholas, TB Murphy, AF McDaid, D Frost Computational Statistics & Data Analysis 54 (3), 711-723, 2010 | 188 | 2010 |
| Mixtures of distance-based models for ranking data TB Murphy, D Martin Computational statistics & data analysis 41 (3), 645-655, 2003 | 187 | 2003 |
| Model‐based clustering of longitudinal data PD McNicholas, TB Murphy Canadian Journal of Statistics 38 (1), 153-168, 2010 | 177 | 2010 |
| Family-Mediated Exercise Intervention (FAME) R Galvin, T Cusack, E O'Grady, TB Murphy, E Stokes Stroke 42 (3), 681-686, 2011 | 173 | 2011 |
| The effect of the GENTLE/s robot-mediated therapy system on arm function after stroke S Coote, B Murphy, W Harwin, E Stokes Clinical rehabilitation 22 (5), 395-405, 2008 | 163 | 2008 |
| Review of statistical network analysis: models, algorithms, and software M Salter-Townshend, A White, I Gollini, TB Murphy Wiley-Blackwell, 2012 | 162 | 2012 |
| Variable selection methods for model-based clustering M Fop, TB Murphy | 153 | 2018 |
| Standardising the lift of an association rule PD McNicholas, TB Murphy, M O'Regan Computational Statistics & Data Analysis 52 (10), 4712-4721, 2008 | 152 | 2008 |
| Exploring Voting Blocs Within the Irish Electorate IC Gormley, TB Murphy Journal of the American Statistical Association 103 (483), 1014-1027, 2008 | 144 | 2008 |
| A mixture of experts model for rank data with applications in election studies IC Gormley, TB Murphy The Annals of Applied Statistics 2 (4), 1452-1477, 2008 | 144 | 2008 |
| Using unlabelled data to update classification rules with applications in food authenticity studies N Dean, TB Murphy, G Downey Journal of the Royal Statistical Society: Series C (Applied Statistics) 55 …, 2006 | 140 | 2006 |
| mclust: Gaussian mixture modelling for model-based clustering, classification, and density estimation C Fraley, AE Raftery, L Scrucca, TB Murphy, M Fop R package version 5 (2), 2016 | 137* | 2016 |
Michael FopLecturer/Assistant Professor University College DublinVerified email at ucd.ie
