| The prevalence of sarcopenia in community-dwelling older adults, an exploration of differences between studies and within definitions: a systematic review and meta-analyses AJ Mayhew, K Amog, S Phillips, G Parise, PD McNicholas, RJ De Souza, ... Age and ageing 48 (1), 48-56, 2019 | 572 | 2019 |
| Parsimonious Gaussian mixture models PD McNicholas, TB Murphy Statistics and Computing 18 (3), 285-296, 2008 | 412 | 2008 |
| Mixture Model-Based Classification PD McNicholas Chapman & Hall/CRC Press, 2016 | 338 | 2016 |
| Model-based clustering PD McNicholas Journal of Classification 33 (3), 331-373, 2016 | 310 | 2016 |
| Model-based clustering of microarray expression data via latent Gaussian mixture models PD McNicholas, TB Murphy Bioinformatics 26 (21), 2705-2712, 2010 | 250 | 2010 |
| A mixture of generalized hyperbolic distributions RP Browne, PD McNicholas Canadian Journal of Statistics 43 (2), 176-198, 2015 | 235 | 2015 |
| Statistical challenges of administrative and transaction data DJ Hand Journal of the Royal Statistical Society Series A: Statistics in Society 181 …, 2018 | 202 | 2018 |
| Mixtures of shifted asymmetriclaplace distributions BC Franczak, RP Browne, PD McNicholas IEEE Transactions on Pattern Analysis and Machine Intelligence 36 (6), 1149-1157, 2013 | 202 | 2013 |
| Model-based clustering, classification, and discriminant analysis via mixtures of multivariate t-distributions: The tEIGEN family JL Andrews, PD McNicholas Statistics and Computing 22 (5), 1021-1029, 2012 | 196 | 2012 |
| 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 |
| Model‐based clustering of longitudinal data PD McNicholas, TB Murphy Canadian Journal of Statistics 38 (1), 153-168, 2010 | 177 | 2010 |
| Muscle androgen receptor content but not systemic hormones is associated with resistance training-induced skeletal muscle hypertrophy in healthy, young men RW Morton, K Sato, MPB Gallaugher, SY Oikawa, PD McNicholas, ... Frontiers in physiology 9, 1373, 2018 | 176 | 2018 |
| Parsimonious mixtures of multivariate contaminated normal distributions A Punzo, PD McNicholas Biometrical Journal 58 (6), 1506-1537, 2016 | 154 | 2016 |
| 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 |
| Extending mixtures of multivariate t-factor analyzers JL Andrews, PD McNicholas Statistics and Computing 21 (3), 361-373, 2011 | 138 | 2011 |
| Model-based classification using latent Gaussian mixture models PD McNicholas Journal of Statistical Planning and Inference 140 (5), 1175-1181, 2010 | 132 | 2010 |
| Estimating common principal components in high dimensions RP Browne, PD McNicholas Advances in Data Analysis and Classification 8 (2), 217-226, 2014 | 122 | 2014 |
| Mixtures of skew-t factor analyzers PM Murray, RP Browne, PD McNicholas Computational Statistics & Data Analysis 77, 326-335, 2014 | 121 | 2014 |
| Finite mixtures of skewed matrix variate distributions MPB Gallaugher, PD McNicholas Pattern Recognition 80, 83-93, 2018 | 119 | 2018 |
| Model-based classification via mixtures of multivariate t-distributions JL Andrews, PD McNicholas, S Subedi Computational Statistics & Data Analysis 55 (1), 520-529, 2011 | 117 | 2011 |
Ryan BrowneUniversity of WaterlooVerified email at uwaterloo.ca
