Paul D. McNicholas

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Ryan BrowneUniversity of WaterlooVerified email at uwaterloo.ca
Michael GallaugherBaylor UniversityVerified email at baylor.edu
Antonio PunzoFull Professor of Statistics, University of CataniaVerified email at unict.it
Brian C. FranczakAssociate Professor of Statistics, MacEwan UniversityVerified email at macewan.ca
Brendan MurphyUniversity College DublinVerified email at ucd.ie
Sanjeena Dang (Subedi)Associate Professor and Canada Research Chair, Carleton UniversityVerified email at math.carleton.ca
Jeffrey L. AndrewsAssociate Professor of Statistics, University of British Columbia - Okanagan CampusVerified email at ubc.ca
Cristina TortoraAssociate Professor San Jose State UniversityVerified email at sjsu.edu
Stuart M PhillipsMcMaster UniversityVerified email at mcmaster.ca
Paula M. MurrayBiostatistician, Children's Hospital Los AngelesVerified email at chla.usc.edu
Parminder RainaProfessor, McMaster UniversityVerified email at mcmaster.ca
Lehana ThabaneProfessor and Associate Chair, Health Research Methods, Evidence, and Impact, McMaster UniversityVerified email at mcmaster.ca
Russell Jude de SouzaAssociate Professor, McMaster UniversityVerified email at mcmaster.ca
Steven RothsteinProfessor of Molecular and Cellular Biology, University of GuelphVerified email at uoguelph.ca
Aaron McDaidIn industry now, after a postdoc in statistical genetics. Might return to bioinformatics!Verified email at ucdconnect.ie
Salvatore IngrassiaFull Professor of Statistics, Università di Catania (Italy)Verified email at unict.it
Utkarsh J. DangCarleton UniversityVerified email at carleton.ca
David M MutchProfessor, University of GuelphVerified email at uoguelph.ca
Aisha ElSherbinyFaculty of Computer Science Dalhousie UniversityVerified email at dal.ca
Irene VrbikUniversity British Columbia OkanaganVerified email at ubc.ca

Paul D. McNicholas

Professor & Canada Research Chair, McMaster University, Ontario, Canada

Verified email at math.mcmaster.ca - Homepage

Classification Computational statistics Mixture models Model-based clustering


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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	484	2019
Parsimonious Gaussian mixture models PD McNicholas, TB Murphy Statistics and Computing 18, 285-296, 2008	389	2008
Mixture Model-Based Classification PD McNicholas Chapman & Hall/CRC Press, 2016	302	2016
Model-based clustering PD McNicholas Journal of Classification 33, 331-373, 2016	277	2016
Model-based clustering of microarray expression data via latent Gaussian mixture models PD McNicholas, TB Murphy Bioinformatics 26 (21), 2705-2712, 2010	243	2010
A mixture of generalized hyperbolic distributions RP Browne, PD McNicholas Canadian Journal of Statistics 43 (2), 176-198, 2015	215	2015
Mixtures of shifted asymmetriclaplace distributions BC Franczak, RP Browne, PD McNicholas IEEE Transactions on Pattern Analysis and Machine Intelligence 36 (6), 1149-1157, 2013	188	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, 1021-1029, 2012	184	2012
Statistical challenges of administrative and transaction data DJ Hand Journal of the Royal Statistical Society Series A: Statistics in Society 181 …, 2018	182	2018
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	175	2010
Model‐based clustering of longitudinal data PD McNicholas, TB Murphy Canadian Journal of Statistics 38 (1), 153-168, 2010	160	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	154	2018
Standardising the lift of an association rule PD McNicholas, TB Murphy, M O’Regan Computational Statistics & Data Analysis 52 (10), 4712-4721, 2008	151	2008
Parsimonious mixtures of multivariate contaminated normal distributions A Punzo, PD McNicholas Biometrical Journal 58 (6), 1506-1537, 2016	137	2016
Extending mixtures of multivariate t-factor analyzers JL Andrews, PD McNicholas Statistics and Computing 21, 361-373, 2011	129	2011
Model-based classification using latent Gaussian mixture models PD McNicholas Journal of Statistical Planning and Inference 140 (5), 1175-1181, 2010	126	2010
Estimating common principal components in high dimensions RP Browne, PD McNicholas Advances in Data Analysis and Classification 8, 217-226, 2014	116	2014
Mixtures of skew-t factor analyzers PM Murray, RP Browne, PD McNicholas Computational Statistics & Data Analysis 77, 326-335, 2014	114	2014
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	108	2016
Model-based classification via mixtures of multivariate t-distributions JL Andrews, PD McNicholas, S Subedi Computational Statistics & Data Analysis 55 (1), 520-529, 2011	108	2011

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