Paul D. McNicholas

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 54

Top Topics

Dimension Reduction

Unsupervised Learning

Factor Analyzers

Top Venues

Comput. Stat. Data Anal.

Adv. Data Anal. Classif.

Pattern Recognit. Lett.

Publications

Paul D. McNicholas
Editorial: Journal of Classification Vol. 41-1. J. Classif. 41 (1) (2024)
Katharine M. Clark, Paul D. McNicholas
Finding Outliers in Gaussian Model-based Clustering. J. Classif. 41 (2) (2024)
Paul D. McNicholas
Editorial: Journal of Classification Vol. 41-2. J. Classif. 41 (2) (2024)
Paul D. McNicholas
Editorial: Journal of Classification Vol. 40-1. J. Classif. 40 (1) (2023)
Katharine M. Clark, Paul D. McNicholas
Clustering Three-Way Data with Outliers. CoRR (2023)
Paul D. McNicholas
Editorial: Journal of Classification Vol. 40-3. J. Classif. 40 (3) (2023)
Anjali Silva, Xiaoke Qin, Steven J. Rothstein, Paul D. McNicholas, Sanjeena Subedi
Finite mixtures of matrix variate Poisson-log normal distributions for three-way count data. Bioinform. 39 (5) (2023)
Michael P. B. Gallaugher, Christophe Biernacki, Paul D. McNicholas
Parameter-wise co-clustering for high-dimensional data. Comput. Stat. 38 (3) (2023)
Paul D. McNicholas
Editorial: Journal of Classification Vol. 40-2. J. Classif. 40 (2) (2023)
Utkarsh J. Dang, Michael P. B. Gallaugher, Ryan P. Browne, Paul D. McNicholas
Model-Based Clustering and Classification Using Mixtures of Multivariate Skewed Power Exponential Distributions. J. Classif. 40 (1) (2023)
Paul D. McNicholas
Editorial: Journal of Classification Vol. 39-3. J. Classif. 39 (3) (2022)
Paul D. McNicholas
Editorial: Journal of Classification Vol. 39-1. J. Classif. 39 (1) (2022)
Michael P. B. Gallaugher, Salvatore D. Tomarchio, Paul D. McNicholas, Antonio Punzo
Correction to: Multivariate cluster weighted models using skewed distributions. Adv. Data Anal. Classif. 16 (4) (2022)
Paul D. McNicholas
Editorial: Journal of Classification Vol. 39-2. J. Classif. 39 (2) (2022)
Michael P. B. Gallaugher, Salvatore D. Tomarchio, Paul D. McNicholas, Antonio Punzo
Multivariate cluster weighted models using skewed distributions. Adv. Data Anal. Classif. 16 (1) (2022)
Salvatore D. Tomarchio, Michael P. B. Gallaugher, Antonio Punzo, Paul D. McNicholas
Mixtures of Matrix-Variate Contaminated Normal Distributions. J. Comput. Graph. Stat. 31 (1) (2022)
Paul D. McNicholas
Editorial: Journal of Classification Vol. 38-3. J. Classif. 38 (3) (2021)
Salvatore D. Tomarchio, Paul D. McNicholas, Antonio Punzo
Matrix Normal Cluster-Weighted Models. J. Classif. 38 (3) (2021)
Sharon M. McNicholas, Paul D. McNicholas, Daniel A. Ashlock
An Evolutionary Algorithm with Crossover and Mutation for Model-Based Clustering. J. Classif. 38 (2) (2021)
Sanjeena Subedi, Paul D. McNicholas
A Variational Approximations-DIC Rubric for Parameter Estimation and Mixture Model Selection Within a Family Setting. J. Classif. 38 (1) (2021)
Paul D. McNicholas
Editorial: Journal of Classification Vol. 38-1. J. Classif. 38 (1) (2021)
Cristina Tortora, Ryan P. Browne, Aisha Elsherbiny, Brian C. Franczak, Paul D. McNicholas
Model-Based Clustering, Classification, and Discriminant Analysis Using the Generalized Hyperbolic Distribution: MixGHD R package. J. Stat. Softw. 98 (1) (2021)
Tyler Roick, Dimitris Karlis, Paul D. McNicholas
Clustering discrete-valued time series. Adv. Data Anal. Classif. 15 (1) (2021)
Paul D. McNicholas
Editorial: Journal of Classification Vol. 38-2. J. Classif. 38 (2) (2021)
Paul D. McNicholas, Douglas L. Steinley
Editorial: Journal of Classification Vol. 37-2. J. Classif. 37 (2) (2020)
Antonio Punzo, Martin Blostein, Paul D. McNicholas
High-dimensional unsupervised classification via parsimonious contaminated mixtures. Pattern Recognit. 98 (2020)
Yuhong Wei, Yang Tang, Paul D. McNicholas
Flexible High-Dimensional Unsupervised Learning with Missing Data. IEEE Trans. Pattern Anal. Mach. Intell. 42 (3) (2020)
Michael P. B. Gallaugher, Paul D. McNicholas
Mixtures of skewed matrix variate bilinear factor analyzers. Adv. Data Anal. Classif. 14 (2) (2020)
Paula M. Murray, Ryan P. Browne, Paul D. McNicholas
Mixtures of Hidden Truncation Hyperbolic Factor Analyzers. J. Classif. 37 (2) (2020)
Cristina Tortora, Paul D. McNicholas, Francesco Palumbo
A Probabilistic Distance Clustering Algorithm Using Gaussian and Student-t Multivariate Density Distributions. SN Comput. Sci. 1 (1) (2020)
Paul D. McNicholas
Editorial: Journal of Classification Vol. 37-3. J. Classif. 37 (3) (2020)
Jochen Einbeck, John Hinde, Salvatore Ingrassia, Tsung-I Lin, Paul D. McNicholas
Editorial for the 4th Special Issue on advances in mixture models. Comput. Stat. Data Anal. 132 (2019)
Michael P. B. Gallaugher, Paul D. McNicholas
On Fractionally-Supervised Classification: Weight Selection and Extension to the Multivariate t-Distribution. J. Classif. 36 (2) (2019)
Yuhong Wei, Yang Tang, Paul D. McNicholas
Mixtures of generalized hyperbolic distributions and mixtures of skew-t distributions for model-based clustering with incomplete data. Comput. Stat. Data Anal. 130 (2019)
Cristina Tortora, Brian C. Franczak, Ryan P. Browne, Paul D. McNicholas
A Mixture of Coalesced Generalized Hyperbolic Distributions. J. Classif. 36 (1) (2019)
Katherine Morris, Antonio Punzo, Paul D. McNicholas, Ryan P. Browne
Asymmetric clusters and outliers: Mixtures of multivariate contaminated shifted asymmetric Laplace distributions. Comput. Stat. Data Anal. 132 (2019)
Anjali Silva, Steven J. Rothstein, Paul D. McNicholas, Sanjeena Subedi
A multivariate Poisson-log normal mixture model for clustering transcriptome sequencing data. BMC Bioinform. 20 (1) (2019)
Paula M. Murray, Ryan P. Browne, Paul D. McNicholas
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. 171 (2019)
Mateen Shaikh, Paul D. McNicholas, Maria-Luiza Antonie, Thomas Brendan Murphy
Standardizing interestingness measures for association rules. Stat. Anal. Data Min. 11 (6) (2018)
Angelina Pesevski, Brian C. Franczak, Paul D. McNicholas
distribution. Pattern Recognit. Lett. 112 (2018)
Hans A. Kestler, Paul D. McNicholas, Adalbert F. X. Wilhelm
Special issue on "Science of big data: theory, methods and applications" - Preface by the Guest Editors. Adv. Data Anal. Classif. 12 (4) (2018)
Michael P. B. Gallaugher, Paul D. McNicholas
Finite mixtures of skewed matrix variate distributions. Pattern Recognit. 80 (2018)
Michael P. B. Gallaugher, Christophe Biernacki, Paul D. McNicholas
Relaxing the Identically Distributed Assumption in Gaussian Co-Clustering for High Dimensional Data. CoRR (2018)
Monica H. T. Wong, David M. Mutch, Paul D. McNicholas
Two-way learning with one-way supervision for gene expression data. BMC Bioinform. 18 (1) (2017)
Michael A. Skinnider, Chris A. Dejong, Brian C. Franczak, Paul D. McNicholas, Nathan A. Magarvey
Comparative analysis of chemical similarity methods for modular natural products with a hypothetical structure enumeration algorithm. J. Cheminformatics 9 (1) (2017)
Paula M. Murray, Ryan P. Browne, Paul D. McNicholas
Hidden truncation hyperbolic distributions, finite mixtures thereof, and their application for clustering. J. Multivar. Anal. 161 (2017)
Antonio Punzo, Paul D. McNicholas
Robust Clustering in Regression Analysis via the Contaminated Gaussian Cluster-Weighted Model. J. Classif. 34 (2) (2017)
Utkarsh J. Dang, Antonio Punzo, Paul D. McNicholas, Salvatore Ingrassia, Ryan P. Browne
Multivariate Response and Parsimony for Gaussian Cluster-Weighted Models. J. Classif. 34 (1) (2017)
Cristina Tortora, Paul D. McNicholas, Ryan P. Browne
A mixture of generalized hyperbolic factor analyzers. Adv. Data Anal. Classif. 10 (4) (2016)
Katherine Morris, Paul D. McNicholas
Clustering, classification, discriminant analysis, and dimension reduction via generalized hyperbolic mixtures. Comput. Stat. Data Anal. 97 (2016)
Adrian O'Hagan, Thomas Brendan Murphy, Isobel Claire Gormley, Paul D. McNicholas, Dimitris Karlis
Clustering with the multivariate normal inverse Gaussian distribution. Comput. Stat. Data Anal. 93 (2016)
John Hinde, Salvatore Ingrassia, Tsung-I Lin, Paul D. McNicholas
The Third Special Issue on Advances in Mixture Models. Comput. Stat. Data Anal. 93 (2016)
Amay S. M. Cheam, Paul D. McNicholas
Modelling receiver operating characteristic curves using Gaussian mixtures. Comput. Stat. Data Anal. 93 (2016)
Paul D. McNicholas
Model-Based Clustering. J. Classif. 33 (3) (2016)
Yang Tang, Ryan P. Browne, Paul D. McNicholas
Model based clustering of high-dimensional binary data. Comput. Stat. Data Anal. 87 (2015)
Yuhong Wei, Paul D. McNicholas
Mixture model averaging for clustering. Adv. Data Anal. Classif. 9 (2) (2015)
Brian C. Franczak, Cristina Tortora, Ryan P. Browne, Paul D. McNicholas
Corrigendum to "Unsupervised learning via mixtures of skewed distributions with hypercube contours" [Pattern Recognition Letters. 58(1), 69-76]. Pattern Recognit. Lett. 62 (2015)
Sanjeena Subedi, Antonio Punzo, Salvatore Ingrassia, Paul D. McNicholas
Cluster-weighted t-factor analyzers for robust model-based clustering and dimension reduction. Stat. Methods Appl. 24 (4) (2015)
Brian C. Franczak, Cristina Tortora, Ryan P. Browne, Paul D. McNicholas
Unsupervised learning via mixtures of skewed distributions with hypercube contours. Pattern Recognit. Lett. 58 (2015)
Irene Vrbik, Paul D. McNicholas
Fractionally-Supervised Classification. J. Classif. 32 (3) (2015)
Jeffrey L. Andrews, Paul D. McNicholas
Variable Selection for Clustering and Classification. J. Classif. 31 (2) (2014)
Sakyajit Bhattacharya, Paul D. McNicholas
A LASSO-penalized BIC for mixture model selection. Adv. Data Anal. Classif. 8 (1) (2014)
Ryan P. Browne, Paul D. McNicholas
Orthogonal Stiefel manifold optimization for eigen-decomposed covariance parameter estimation in mixture models. Stat. Comput. 24 (2) (2014)
Brian C. Franczak, Ryan P. Browne, Paul D. McNicholas
Mixtures of Shifted AsymmetricLaplace Distributions. IEEE Trans. Pattern Anal. Mach. Intell. 36 (6) (2014)
Irene Vrbik, Paul D. McNicholas
Parsimonious skew mixture models for model-based clustering and classification. Comput. Stat. Data Anal. 71 (2014)
Sanjeena Subedi, Paul D. McNicholas
Variational Bayes approximations for clustering via mixtures of normal inverse Gaussian distributions. Adv. Data Anal. Classif. 8 (2) (2014)
Ryan P. Browne, Paul D. McNicholas
Estimating common principal components in high dimensions. Adv. Data Anal. Classif. 8 (2) (2014)
Paula M. Murray, Ryan P. Browne, Paul D. McNicholas
Mixtures of skew-t factor analyzers. Comput. Stat. Data Anal. 77 (2014)
Yu Xia, Paul D. McNicholas
A gradient method for the monotone fused least absolute shrinkage and selection operator. Optim. Methods Softw. 29 (3) (2014)
Dankmar Böhning, Christian Hennig, Geoffrey J. McLachlan, Paul D. McNicholas
The 2nd special issue on advances in mixture models. Comput. Stat. Data Anal. 71 (2014)
Paul D. McNicholas, Ryan P. Browne, Paula M. Murray
Discussion of 'Model-based clustering and classification with non-normal mixture distributions' by Lee and McLachlan. Stat. Methods Appl. 22 (4) (2013)
Jeffrey L. Andrews, Paul D. McNicholas
Using evolutionary algorithms for model-based clustering. Pattern Recognit. Lett. 34 (9) (2013)
Katherine Morris, Paul D. McNicholas, Luca Scrucca
Dimension reduction for model-based clustering via mixtures of multivariate $$t$$ t -distributions. Adv. Data Anal. Classif. 7 (3) (2013)
Sanjeena Subedi, Antonio Punzo, Salvatore Ingrassia, Paul D. McNicholas
Clustering and classification via cluster-weighted factor analyzers. Adv. Data Anal. Classif. 7 (1) (2013)
Michelle A. Steane, Paul D. McNicholas, Rickey Y. Yada
-Factor Analyzers. Commun. Stat. Simul. Comput. 41 (4) (2012)
Zeny Z. Feng, Xiaojian Yang, Sanjeena Subedi, Paul D. McNicholas
The LASSO and Sparse Least Squares Regression Methods for SNP Selection in Predicting Quantitative Traits. IEEE ACM Trans. Comput. Biol. Bioinform. 9 (2) (2012)
Jeffrey L. Andrews, Paul D. McNicholas
Model-based clustering, classification, and discriminant analysis via mixtures of multivariate t-distributions - The tEIGEN family. Stat. Comput. 22 (5) (2012)
Ryan P. Browne, Paul D. McNicholas, Matthew D. Sparling
Model-Based Learning Using a Mixture of Mixtures of Gaussian and Uniform Distributions. IEEE Trans. Pattern Anal. Mach. Intell. 34 (4) (2012)
Daniel A. Ashlock, Justin Schonfeld, Paul D. McNicholas
Translation tables: A genetic code in a evolutionary algorithm. IEEE Congress on Evolutionary Computation (2011)
Jeffrey L. Andrews, Paul D. McNicholas, Sanjeena Subedi
Model-based classification via mixtures of multivariate t-distributions. Comput. Stat. Data Anal. 55 (1) (2011)
Jeffrey L. Andrews, Paul D. McNicholas
-factor analyzers. Stat. Comput. 21 (3) (2011)