Paul D. McNicholas

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Citations	4861	3456
h-index	40	35
i10-index	92	86

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Ryan BrowneUniversity of WaterlooVerified email at uwaterloo.ca
Brendan MurphyUniversity College DublinVerified email at ucd.ie
Antonio PunzoFull Professor of Statistics, University of CataniaVerified email at unict.it
Brian C. FranczakMacEwan UniversityVerified email at macewan.ca
Sanjeena Dang (Subedi)Carleton UniversityVerified email at math.carleton.ca
Jeffrey L. AndrewsAssociate Professor of Statistics, University of British Columbia - Okanagan CampusVerified email at ubc.ca
Cristina TortoraAssistant Professor San Jose State UniversityVerified email at sjsu.edu
Paula M. MurrayUniversity of GuelphVerified email at uoguelph.ca
Stuart M PhillipsMcMaster UniversityVerified email at mcmaster.ca
Salvatore IngrassiaFull Professor of Statistics, Università di Catania (Italy)Verified email at unict.it
Aaron McDaidResearch student, UCD DublinVerified email at ucdconnect.ie
Katherine MorrisOntario College of PharmacistsVerified email at ocpinfo.com
Steven RothsteinProfessor of Molecular and Cellular Biology, University of GuelphVerified email at uoguelph.ca
Utkarsh J. DangCarleton UniversityVerified email at carleton.ca
David M MutchAssociate Professor, University of GuelphVerified email at uoguelph.ca
Irene VrbikUniversity British Columbia OkanaganVerified email at ubc.ca
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
Alexandra MayhewMcMaster UniversityVerified email at mcmaster.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


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Parsimonious Gaussian mixture models PD McNicholas, TB Murphy Statistics and Computing 18 (3), 285-296, 2008	276	2008
Model-based clustering of microarray expression data via latent Gaussian mixture models PD McNicholas, TB Murphy Bioinformatics 26 (21), 2705-2712, 2010	194	2010
Mixture Model-Based Classification PD McNicholas Chapman & Hall/CRC Press, 2016	162	2016
Model-based clustering, classification, and discriminant analysis via mixtures of multivariate t-distributions JL Andrews, PD McNicholas Statistics and Computing 22 (5), 1021-1029, 2012	144	2012
A mixture of generalized hyperbolic distributions RP Browne, PD McNicholas Canadian Journal of Statistics 43 (2), 176-198, 2015	141	2015
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	139	2010
Mixtures of shifted asymmetriclaplace distributions BC Franczak, RP Browne, PD McNicholas IEEE Transactions on Pattern Analysis and Machine Intelligence 36 (6), 1149-1157, 2013	135	2013
Model-based clustering PD McNicholas Journal of Classification 33 (3), 331-373, 2016	129	2016
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	119	2019
Model‐based clustering of longitudinal data PD McNicholas, TB Murphy Canadian Journal of Statistics 38 (1), 153-168, 2010	112	2010
Extending mixtures of multivariate t-factor analyzers JL Andrews, PD McNicholas Statistics and Computing 21 (3), 361-373, 2011	109	2011
Model-based classification using latent Gaussian mixture models PD McNicholas Journal of Statistical Planning and Inference 140 (5), 1175-1181, 2010	96	2010
Mixtures of skew-t factor analyzers PM Murray, RP Browne, PD McNicholas Computational Statistics & Data Analysis 77, 326-335, 2014	91	2014
Analytic calculations for the EM algorithm for multivariate skew-t mixture models I Vrbik, PD McNicholas Statistics & Probability Letters 82 (6), 1169-1174, 2012	88	2012
Standardising the lift of an association rule PD McNicholas, TB Murphy, M O’Regan Computational Statistics & Data Analysis 52 (10), 4712-4721, 2008	87	2008
Parsimonious skew mixture models for model-based clustering and classification I Vrbik, PD McNicholas Computational Statistics & Data Analysis 71, 196-210, 2014	84	2014
Model-based learning using a mixture of mixtures of Gaussian and uniform distributions RP Browne, PD McNicholas, MD Sparling IEEE Transactions on Pattern Analysis and Machine Intelligence 34 (4), 814-817, 2011	80	2011
Estimating common principal components in high dimensions RP Browne, PD McNicholas Advances in Data Analysis and Classification 8 (2), 217-226, 2014	75	2014
Model-based classification via mixtures of multivariate t-distributions JL Andrews, PD McNicholas, S Subedi Computational Statistics & Data Analysis 55 (1), 520-529, 2011	75	2011
Genome-wide expression profiling of maize in response to individual and combined water and nitrogen stresses S Humbert, S Subedi, J Cohn, B Zeng, YM Bi, X Chen, T Zhu, ... BMC genomics 14 (1), 1-13, 2013	74	2013

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