Paul D. McNicholas - Google Scholar Citations

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	All	Since 2015
Citations	4017	2954
h-index	36	33
i10-index	81	77

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Co-authors

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
Jeffrey L. AndrewsAssistant Professor of Statistics, University of British Columbia - Okanagan CampusVerified email at ubc.ca
Sanjeena Dang (Subedi)Binghamton UniversityVerified email at binghamton.edu
Cristina TortoraAssistant Professor San Jose State UniversityVerified email at sjsu.edu
Paula M. MurrayUniversity of GuelphVerified email at uoguelph.ca
Aaron McDaidResearch student, UCD DublinVerified email at ucdconnect.ie
Salvatore IngrassiaFull Professor of Statistics, Università di Catania (Italy)Verified email at unict.it
Katherine MorrisOntario College of PharmacistsVerified email at ocpinfo.com
Steven RothsteinProfessor of Molecular and Cellular Biology, University of GuelphVerified email at uoguelph.ca
David M MutchAssociate Professor, University of GuelphVerified email at uoguelph.ca
Irene VrbikMcGill UniversityVerified email at mcgill.ca
Utkarsh J. DangBinghamton University, SUNYVerified email at binghamton.edu
Stuart M PhillipsMcMaster UniversityVerified email at mcmaster.ca
Tsung-l LinInstitute of Statistics, National Chung Hsing UniversityVerified email at nchu.edu.tw
Sharon McNicholasMcMaster UniversityVerified email at uoguelph.ca
Dermot FrostTrinity College, DublinVerified email at tcd.ie
Dimitris KarlisProfessor, Dept of Statistics, Athens University of Economics and BusinessVerified email at aueb.gr

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	249	2008
Model-based clustering of microarray expression data via latent Gaussian mixture models PD McNicholas, TB Murphy Bioinformatics 26 (21), 2705-2712, 2010	179	2010
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	132	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	130	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	117	2013
Mixture Model-Based Classification PD McNicholas Chapman & Hall/CRC Press, 2016	111	2016
A mixture of generalized hyperbolic distributions RP Browne, PD McNicholas Canadian Journal of Statistics 43 (2), 176-198, 2015	109	2015
Extending mixtures of multivariate t-factor analyzers JL Andrews, PD Mcnicholas Statistics and Computing 21 (3), 361-373, 2011	106	2011
Model‐based clustering of longitudinal data PD McNicholas, TB Murphy Canadian Journal of Statistics 38 (1), 153-168, 2010	99	2010
Model-based clustering PD McNicholas Journal of Classification 33 (3), 331-373, 2016	93	2016
Model-based classification using latent Gaussian mixture models PD McNicholas Journal of Statistical Planning and Inference 140 (5), 1175-1181, 2010	84	2010
Analytic calculations for the EM algorithm for multivariate skew-t mixture models I Vrbik, PD McNicholas Statistics & Probability Letters 82 (6), 1169-1174, 2012	82	2012
Mixtures of skew-t factor analyzers PM Murray, RP Browne, PD McNicholas Computational Statistics & Data Analysis 77, 326-335, 2014	78	2014
Parsimonious skew mixture models for model-based clustering and classification I Vrbik, PD Mcnicholas Computational Statistics & Data Analysis 71, 196-210, 2014	75	2014
Standardising the lift of an association rule PD McNicholas, TB Murphy, M O’Regan Computational Statistics & Data Analysis 52 (10), 4712-4721, 2008	73	2008
Estimating common principal components in high dimensions RP Browne, PD Mcnicholas Advances in Data Analysis and Classification 8 (2), 217-226, 2014	71	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	68	2011
Model-based classification via mixtures of multivariate t-distributions JL Andrews, PD McNicholas, S Subedi Computational Statistics & Data Analysis 55 (1), 520-529, 2011	68	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), 3, 2013	65	2013
Narrowband UVB and PUVA in the treatment of mycosis fungoides: a retrospective study K Ahmad, S Rogers, PD McNicholas, P Collins Acta dermato-venereologica 87 (5), 413-417, 2007	65	2007

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