Paul D. McNicholas

Orcid: 0000-0002-2482-523X

Affiliations:
  • McMaster University, Department of Mathematics and Statistics, Hamilton, Canada
  • University of Guelph, Canada


According to our database1, Paul D. McNicholas authored at least 83 papers between 2008 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2023
Editorial: Journal of Classification Vol. 40-3.
J. Classif., November, 2023

Parameter-wise co-clustering for high-dimensional data.
Comput. Stat., September, 2023

Editorial: Journal of Classification Vol. 40-2.
J. Classif., July, 2023

Finite mixtures of matrix variate Poisson-log normal distributions for three-way count data.
Bioinform., May, 2023

Editorial: Journal of Classification Vol. 40-1.
J. Classif., April, 2023

Model-Based Clustering and Classification Using Mixtures of Multivariate Skewed Power Exponential Distributions.
J. Classif., April, 2023

Clustering Three-Way Data with Outliers.
CoRR, 2023

2022
Mixtures of Matrix-Variate Contaminated Normal Distributions.
J. Comput. Graph. Stat., January, 2022

Editorial: Journal of Classification Vol. 39-3.
J. Classif., 2022

Editorial: Journal of Classification Vol. 39-2.
J. Classif., 2022

Editorial: Journal of Classification Vol. 39-1.
J. Classif., 2022

Correction to: Multivariate cluster weighted models using skewed distributions.
Adv. Data Anal. Classif., 2022

Multivariate cluster weighted models using skewed distributions.
Adv. Data Anal. Classif., 2022

2021
Model-Based Clustering, Classification, and Discriminant Analysis Using the Generalized Hyperbolic Distribution: MixGHD R package.
J. Stat. Softw., 2021

Matrix Normal Cluster-Weighted Models.
J. Classif., 2021

A Variational Approximations-DIC Rubric for Parameter Estimation and Mixture Model Selection Within a Family Setting.
J. Classif., 2021

An Evolutionary Algorithm with Crossover and Mutation for Model-Based Clustering.
J. Classif., 2021

Editorial: Journal of Classification Vol. 38-3.
J. Classif., 2021

Editorial: Journal of Classification Vol. 38-2.
J. Classif., 2021

Editorial: Journal of Classification Vol. 38-1.
J. Classif., 2021

Clustering discrete-valued time series.
Adv. Data Anal. Classif., 2021

2020
A Probabilistic Distance Clustering Algorithm Using Gaussian and Student-t Multivariate Density Distributions.
SN Comput. Sci., 2020

High-dimensional unsupervised classification via parsimonious contaminated mixtures.
Pattern Recognit., 2020

Flexible High-Dimensional Unsupervised Learning with Missing Data.
IEEE Trans. Pattern Anal. Mach. Intell., 2020

Mixtures of Hidden Truncation Hyperbolic Factor Analyzers.
J. Classif., 2020

Editorial: Journal of Classification Vol. 37-2.
J. Classif., 2020

Editorial: Journal of Classification Vol. 37-3.
J. Classif., 2020

Mixtures of skewed matrix variate bilinear factor analyzers.
Adv. Data Anal. Classif., 2020

2019
Note of Clarification on 'Hidden truncation hyperbolic distributions, finite mixtures thereof, and their application for clustering', by Murray, Browne, and McNicholas, J. Multivariate Anal. 161 (2017) 141-156.
J. Multivar. Anal., 2019

Mixtures of generalized hyperbolic distributions and mixtures of skew-t distributions for model-based clustering with incomplete data.
Comput. Stat. Data Anal., 2019

Asymmetric clusters and outliers: Mixtures of multivariate contaminated shifted asymmetric Laplace distributions.
Comput. Stat. Data Anal., 2019

Editorial for the 4th Special Issue on advances in mixture models.
Comput. Stat. Data Anal., 2019

A Mixture of Coalesced Generalized Hyperbolic Distributions.
J. Classif., 2019

On Fractionally-Supervised Classification: Weight Selection and Extension to the Multivariate t-Distribution.
J. Classif., 2019

A multivariate Poisson-log normal mixture model for clustering transcriptome sequencing data.
BMC Bioinform., 2019

2018
Standardizing interestingness measures for association rules.
Stat. Anal. Data Min., 2018

Subspace clustering with the multivariate-<i>t</i> distribution.
Pattern Recognit. Lett., 2018

Finite mixtures of skewed matrix variate distributions.
Pattern Recognit., 2018

Relaxing the Identically Distributed Assumption in Gaussian Co-Clustering for High Dimensional Data.
CoRR, 2018

Special issue on "Science of big data: theory, methods and applications" - Preface by the Guest Editors.
Adv. Data Anal. Classif., 2018

2017
Hidden truncation hyperbolic distributions, finite mixtures thereof, and their application for clustering.
J. Multivar. Anal., 2017

Comparative analysis of chemical similarity methods for modular natural products with a hypothetical structure enumeration algorithm.
J. Cheminformatics, 2017

Robust Clustering in Regression Analysis via the Contaminated Gaussian Cluster-Weighted Model.
J. Classif., 2017

Multivariate Response and Parsimony for Gaussian Cluster-Weighted Models.
J. Classif., 2017

Two-way learning with one-way supervision for gene expression data.
BMC Bioinform., 2017

2016
Clustering with the multivariate normal inverse Gaussian distribution.
Comput. Stat. Data Anal., 2016

Clustering, classification, discriminant analysis, and dimension reduction via generalized hyperbolic mixtures.
Comput. Stat. Data Anal., 2016

The Third Special Issue on Advances in Mixture Models.
Comput. Stat. Data Anal., 2016

Modelling receiver operating characteristic curves using Gaussian mixtures.
Comput. Stat. Data Anal., 2016

Model-Based Clustering.
J. Classif., 2016

A mixture of generalized hyperbolic factor analyzers.
Adv. Data Anal. Classif., 2016

2015
Cluster-weighted t-factor analyzers for robust model-based clustering and dimension reduction.
Stat. Methods Appl., 2015

Corrigendum to "Unsupervised learning via mixtures of skewed distributions with hypercube contours" [Pattern Recognition Letters. 58(1), 69-76].
Pattern Recognit. Lett., 2015

Unsupervised learning via mixtures of skewed distributions with hypercube contours.
Pattern Recognit. Lett., 2015

Model based clustering of high-dimensional binary data.
Comput. Stat. Data Anal., 2015

Fractionally-Supervised Classification.
J. Classif., 2015

Mixture model averaging for clustering.
Adv. Data Anal. Classif., 2015

2014
Orthogonal Stiefel manifold optimization for eigen-decomposed covariance parameter estimation in mixture models.
Stat. Comput., 2014

Mixtures of Shifted AsymmetricLaplace Distributions.
IEEE Trans. Pattern Anal. Mach. Intell., 2014

A gradient method for the monotone fused least absolute shrinkage and selection operator.
Optim. Methods Softw., 2014

Parsimonious skew mixture models for model-based clustering and classification.
Comput. Stat. Data Anal., 2014

Mixtures of skew-t factor analyzers.
Comput. Stat. Data Anal., 2014

The 2nd special issue on advances in mixture models.
Comput. Stat. Data Anal., 2014

Variable Selection for Clustering and Classification.
J. Classif., 2014

Variational Bayes approximations for clustering via mixtures of normal inverse Gaussian distributions.
Adv. Data Anal. Classif., 2014

Estimating common principal components in high dimensions.
Adv. Data Anal. Classif., 2014

A LASSO-penalized BIC for mixture model selection.
Adv. Data Anal. Classif., 2014

2013
On Clustering and Classification Via Mixtures of Multivariate t-Distributions.
Proceedings of the Statistical Models for Data Analysis, 2013

Discussion of 'Model-based clustering and classification with non-normal mixture distributions' by Lee and McLachlan.
Stat. Methods Appl., 2013

Using evolutionary algorithms for model-based clustering.
Pattern Recognit. Lett., 2013

Clustering and classification via cluster-weighted factor analyzers.
Adv. Data Anal. Classif., 2013

Dimension reduction for model-based clustering via mixtures of multivariate $$t$$ t -distributions.
Adv. Data Anal. Classif., 2013

2012
The LASSO and Sparse Least Squares Regression Methods for SNP Selection in Predicting Quantitative Traits.
IEEE ACM Trans. Comput. Biol. Bioinform., 2012

Model-based clustering, classification, and discriminant analysis via mixtures of multivariate t-distributions - The tEIGEN family.
Stat. Comput., 2012

Model-Based Learning Using a Mixture of Mixtures of Gaussian and Uniform Distributions.
IEEE Trans. Pattern Anal. Mach. Intell., 2012

Model-Based Classification via Mixtures of Multivariate <i>t</i>-Factor Analyzers.
Commun. Stat. Simul. Comput., 2012

2011
Extending mixtures of multivariate <i>t</i>-factor analyzers.
Stat. Comput., 2011

Model-based classification via mixtures of multivariate t-distributions.
Comput. Stat. Data Anal., 2011

Translation tables: A genetic code in a evolutionary algorithm.
Proceedings of the IEEE Congress on Evolutionary Computation, 2011

2010
Serial and parallel implementations of model-based clustering via parsimonious Gaussian mixture models.
Comput. Stat. Data Anal., 2010

Model-based clustering of microarray expression data via latent Gaussian mixture models.
Bioinform., 2010

2008
Parsimonious Gaussian mixture models.
Stat. Comput., 2008

Standardising the lift of an association rule.
Comput. Stat. Data Anal., 2008


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