2026 Paul D. McNicholas: Mathematics Researcher – H-Index, Publications & Awards

D-Index & Metrics

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Mathematics	45	1509	1303	55	49	191	6502
Engineering and Technology	46	5265	5075	211	202	197	6804

Discipline name

D-Index

World Ranking

Current World Ranking

National Ranking

Current National Ranking

Publications

Citations

Mathematics

1509

1303

191

6502

Engineering and Technology

5265

5075

211

202

197

6804

Mathematics

D-Index

Citations

6502

World Ranking

1509

National Ranking

Engineering and Technology

D-Index

Citations

6804

World Ranking

5265

National Ranking

211

Overview

Paul D. McNicholas is affiliated with McMaster University in Canada, conducting research primarily within computer science. Their work spans several subfields, notably artificial intelligence, statistics and probability, computer vision and pattern recognition, physiology, and molecular biology.

The scientist's research focuses on topics including Bayesian methods and mixture models, advanced clustering algorithms, image retrieval and classification techniques, statistical methods and Bayesian inference, statistical methods and inference, gene expression and cancer classification, and nutrition and health in aging.

Among the recent papers published are:

Trajectories of Symptom Severity in Children with Autism: Variability and Turning Points through the Transition to School (2021, Journal of Autism and Developmental Disorders)
Mixtures of Matrix-Variate Contaminated Normal Distributions (2021, Journal of Computational and Graphical Statistics)
Model-Based Clustering, Classification, and Discriminant Analysis Using the Generalized Hyperbolic Distribution: MixGHD R package (2021, Journal of Statistical Software)
The impact of different diagnostic criteria on the association of sarcopenia with injurious falls in the CLSA (2020, Journal of Cachexia Sarcopenia and Muscle)
Identification of five important genes to predict glioblastoma subtypes (2021, Neuro-Oncology Advances)

Frequent co-authors collaborating with Paul D. McNicholas include:

Michael P. B. Gallaugher
Salvatore D. Tomarchio
Antonio Punzo
Parminder Raina
Alexandra Mayhew

The scientist publishes regularly in several venues, with a particular concentration in the following:

Journal of Classification
arXiv (Cornell University)
Canadian Journal of Statistics
Statistics and Computing
Advances in Data Analysis and Classification

Best Publications

The prevalence of sarcopenia in community-dwelling older adults, an exploration of differences between studies and within definitions: a systematic review and meta-analyses.

A J Mayhew;A J Mayhew;K Amog;K Amog;S Phillips;G Parise

463
Citations
Parsimonious Gaussian mixture models

Paul David Mcnicholas;Thomas Brendan Murphy

362
Citations
Mixture Model-Based Classification

Paul D. McNicholas

265
Citations
Model-based clustering of microarray expression data via latent Gaussian mixture models

Paul D. McNicholas;Thomas Brendan Murphy

235
Citations
Model-Based Clustering

Paul D. McNicholas

226
Citations
A mixture of generalized hyperbolic distributions

Ryan P. Browne;Paul D. McNicholas

197
Citations
Model-based clustering, classification, and discriminant analysis via mixtures of multivariate t-distributions

Jeffrey L. Andrews;Paul D. Mcnicholas

186
Citations
Mixtures of Shifted AsymmetricLaplace Distributions

Brian C. Franczak;Ryan P. Browne;Paul D. McNicholas

172
Citations
Genome-wide expression profiling of maize in response to individual and combined water and nitrogen stresses

Sabrina Humbert;Sabrina Humbert;Sanjeena Subedi;Jonathan Cohn;Bin Zeng

170
Citations
Serial and parallel implementations of model-based clustering via parsimonious Gaussian mixture models

P. D. McNicholas;T. B. Murphy;A. F. McDaid;D. Frost

168
Citations
Model-based clustering of longitudinal data

Paul D. McNicholas;T. Brendan Murphy

153
Citations
Muscle Androgen Receptor Content but Not Systemic Hormones Is Associated With Resistance Training-Induced Skeletal Muscle Hypertrophy in Healthy, Young Men

Robert W. Morton;Koji Sato;Michael P. B. Gallaugher;Sara Y. Oikawa

134
Citations
Extending mixtures of multivariate t-factor analyzers

Jeffrey L. Andrews;Paul D. Mcnicholas

131
Citations
Standardising the lift of an association rule

P. D. McNicholas;T. B. Murphy;M. O'Regan

127
Citations
Model-based classification using latent Gaussian mixture models

Paul D. McNicholas

121
Citations
Mixtures of skew-t factor analyzers

Paula M. Murray;Ryan P. Browne;Paul D. McNicholas

113
Citations
Parsimonious mixtures of multivariate contaminated normal distributions.

Antonio Punzo;Paul D. McNicholas

111
Citations
Clustering with the multivariate normal inverse Gaussian distribution

Adrian O'Hagan;Thomas Brendan Murphy;Isobel Claire Gormley;Paul D. McNicholas

103
Citations
Estimating common principal components in high dimensions

Ryan P. Browne;Paul D. Mcnicholas

101
Citations
Model-based classification via mixtures of multivariate t-distributions

Jeffrey L. Andrews;Paul D. McNicholas;Sanjeena Subedi

100
Citations
Parsimonious skew mixture models for model-based clustering and classification

Irene Vrbik;Paul D. McNicholas

97
Citations
Serial and Parallel Implementations of Model-Based Clustering via Parsimonious

P. D. McNicholas;T. B. Murphy;D. Frost

0
Citations

Frequent Co-Authors

Steven J. Rothstein University of Guelph

Marc G. Genton King Abdullah University of Science and Technology

Dimitris Karlis Athens University of Economics and Business

Stuart M. Phillips McMaster University

Adelchi Azzalini University of Padua

Tong Zhu Research Triangle Park Foundation

Lehana Thabane McMaster University

Geoffrey J. McLachlan University of Queensland

Hans A. Kestler University of Ulm

Susan A. Jebb University of Oxford

External Links

Personal website of Paul D. McNicholas Google Scholar page

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