Standardising the lift of an association rule. - Paul David McNicholas; Thomas Brendan Murphy; M. O'Regan (Comput. Stat. Data Anal., 2008)

Parsimonious Gaussian mixture models. - Paul David McNicholas; Thomas Brendan Murphy (Stat. Comput., 2008)

Model-based clustering of microarray expression data via latent Gaussian mixture models. - Paul David McNicholas; Thomas Brendan Murphy (Bioinform., 2010)

Serial and parallel implementations of model-based clustering via parsimonious Gaussian mixture models. - Paul David McNicholas; Thomas Brendan Murphy; Aaron F. McDaid; Dermot Frost (Comput. Stat. Data Anal., 2010)

Translation tables: A genetic code in a evolutionary algorithm. - Daniel A. Ashlock; Justin Schonfeld; Paul D. McNicholas (IEEE Congress on Evolutionary Computation, 2011)

Model-based classification via mixtures of multivariate t-distributions. - Jeffrey L. Andrews; Paul D. McNicholas; Sanjeena Subedi (Comput. Stat. Data Anal., 2011)

Extending mixtures of multivariate t-factor analyzers. - Jeffrey L. Andrews; Paul D. McNicholas (Stat. Comput., 2011)

Model-Based Classification via Mixtures of Multivariate t-Factor Analyzers. - Michelle A. Steane; Paul D. McNicholas; Rickey Y. Yada (Commun. Stat. Simul. Comput., 2012)

Model-Based Learning Using a Mixture of Mixtures of Gaussian and Uniform Distributions. - Ryan P. Browne; Paul D. McNicholas; Matthew D. Sparling (IEEE Trans. Pattern Anal. Mach. Intell., 2012)

Model-based clustering, classification, and discriminant analysis via mixtures of multivariate t-distributions - The tEIGEN family. - Jeffrey L. Andrews; Paul D. McNicholas (Stat. Comput., 2012)

The LASSO and Sparse Least Squares Regression Methods for SNP Selection in Predicting Quantitative Traits. - Zeny Z. Feng; Xiaojian Yang; Sanjeena Subedi; Paul D. McNicholas (IEEE ACM Trans. Comput. Biol. Bioinform., 2012)

Dimension reduction for model-based clustering via mixtures of multivariate $$t$$ t -distributions. - Katherine Morris; Paul D. McNicholas; Luca Scrucca (Adv. Data Anal. Classif., 2013)

Clustering and classification via cluster-weighted factor analyzers. - Sanjeena Subedi; Antonio Punzo; Salvatore Ingrassia; Paul D. McNicholas (Adv. Data Anal. Classif., 2013)

Using evolutionary algorithms for model-based clustering. - Jeffrey L. Andrews; Paul D. McNicholas (Pattern Recognit. Lett., 2013)

Discussion of 'Model-based clustering and classification with non-normal mixture distributions' by Lee and McLachlan. - Paul D. McNicholas; Ryan P. Browne; Paula M. Murray (Stat. Methods Appl., 2013)

On Clustering and Classification Via Mixtures of Multivariate t-Distributions. - Paul D. McNicholas (Statistical Models for Data Analysis, 2013)

A LASSO-penalized BIC for mixture model selection. - Sakyajit Bhattacharya; Paul D. McNicholas (Adv. Data Anal. Classif., 2014)

Estimating common principal components in high dimensions. - Ryan P. Browne; Paul D. McNicholas (Adv. Data Anal. Classif., 2014)

Variational Bayes approximations for clustering via mixtures of normal inverse Gaussian distributions. - Sanjeena Subedi; Paul D. McNicholas (Adv. Data Anal. Classif., 2014)

Variable Selection for Clustering and Classification. - Jeffrey L. Andrews; Paul D. McNicholas (J. Classif., 2014)

The 2nd special issue on advances in mixture models. - Dankmar Böhning; Christian Hennig; Geoffrey J. McLachlan; Paul D. McNicholas (Comput. Stat. Data Anal., 2014)

Mixtures of skew-t factor analyzers. - Paula M. Murray; Ryan P. Browne; Paul D. McNicholas (Comput. Stat. Data Anal., 2014)

Parsimonious skew mixture models for model-based clustering and classification. - Irene Vrbik; Paul D. McNicholas (Comput. Stat. Data Anal., 2014)

A gradient method for the monotone fused least absolute shrinkage and selection operator. - Yu Xia; Paul D. McNicholas (Optim. Methods Softw., 2014)

Mixtures of Shifted AsymmetricLaplace Distributions. - Brian C. Franczak; Ryan P. Browne; Paul D. McNicholas (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

Orthogonal Stiefel manifold optimization for eigen-decomposed covariance parameter estimation in mixture models. - Ryan P. Browne; Paul D. McNicholas (Stat. Comput., 2014)

Mixture model averaging for clustering. - Yuhong Wei; Paul D. McNicholas (Adv. Data Anal. Classif., 2015)

Fractionally-Supervised Classification. - Irene Vrbik; Paul D. McNicholas (J. Classif., 2015)

Model based clustering of high-dimensional binary data. - Yang Tang; Ryan P. Browne; Paul D. McNicholas (Comput. Stat. Data Anal., 2015)

Unsupervised learning via mixtures of skewed distributions with hypercube contours. - Brian C. Franczak; Cristina Tortora; Ryan P. Browne; Paul D. McNicholas (Pattern Recognit. Lett., 2015)

Corrigendum to "Unsupervised learning via mixtures of skewed distributions with hypercube contours" [Pattern Recognition Letters. 58(1), 69-76]. - Brian C. Franczak; Cristina Tortora; Ryan P. Browne; Paul D. McNicholas (Pattern Recognit. Lett., 2015)

Cluster-weighted t-factor analyzers for robust model-based clustering and dimension reduction. - Sanjeena Subedi; Antonio Punzo; Salvatore Ingrassia; Paul D. McNicholas (Stat. Methods Appl., 2015)

A mixture of generalized hyperbolic factor analyzers. - Cristina Tortora; Paul D. McNicholas; Ryan P. Browne (Adv. Data Anal. Classif., 2016)

Model-Based Clustering. - Paul D. McNicholas (J. Classif., 2016)

Modelling receiver operating characteristic curves using Gaussian mixtures. - Amay S. M. Cheam; Paul D. McNicholas (Comput. Stat. Data Anal., 2016)

The Third Special Issue on Advances in Mixture Models. - John Hinde; Salvatore Ingrassia; Tsung-I Lin; Paul D. McNicholas (Comput. Stat. Data Anal., 2016)

Clustering, classification, discriminant analysis, and dimension reduction via generalized hyperbolic mixtures. - Katherine Morris; Paul D. McNicholas (Comput. Stat. Data Anal., 2016)

Clustering with the multivariate normal inverse Gaussian distribution. - Adrian O'Hagan; Thomas Brendan Murphy; Isobel Claire Gormley; Paul D. McNicholas; Dimitris Karlis (Comput. Stat. Data Anal., 2016)

Two-way learning with one-way supervision for gene expression data. - Monica H. T. Wong; David M. Mutch; Paul D. McNicholas (BMC Bioinform., 2017)

Multivariate Response and Parsimony for Gaussian Cluster-Weighted Models. - Utkarsh J. Dang; Antonio Punzo; Paul D. McNicholas; Salvatore Ingrassia; Ryan P. Browne (J. Classif., 2017)

Robust Clustering in Regression Analysis via the Contaminated Gaussian Cluster-Weighted Model. - Antonio Punzo; Paul D. McNicholas (J. Classif., 2017)

Comparative analysis of chemical similarity methods for modular natural products with a hypothetical structure enumeration algorithm. - Michael A. Skinnider; Chris A. Dejong; Brian C. Franczak; Paul D. McNicholas; Nathan A. Magarvey (J. Cheminformatics, 2017)

Hidden truncation hyperbolic distributions, finite mixtures thereof, and their application for clustering. - Paula M. Murray; Ryan P. Browne; Paul D. McNicholas (J. Multivar. Anal., 2017)

Special issue on "Science of big data: theory, methods and applications" - Preface by the Guest Editors. - Hans A. Kestler; Paul D. McNicholas; Adalbert F. X. Wilhelm (Adv. Data Anal. Classif., 2018)

Relaxing the Identically Distributed Assumption in Gaussian Co-Clustering for High Dimensional Data. - Michael P. B. Gallaugher; Christophe Biernacki; Paul D. McNicholas (CoRR, 2018)

Finite mixtures of skewed matrix variate distributions. - Michael P. B. Gallaugher; Paul D. McNicholas (Pattern Recognit., 2018)

Subspace clustering with the multivariate-t distribution. - Angelina Pesevski; Brian C. Franczak; Paul D. McNicholas (Pattern Recognit. Lett., 2018)

Standardizing interestingness measures for association rules. - Mateen Shaikh; Paul D. McNicholas; Maria-Luiza Antonie; Thomas Brendan Murphy (Stat. Anal. Data Min., 2018)

A multivariate Poisson-log normal mixture model for clustering transcriptome sequencing data. - Anjali Silva; Steven J. Rothstein; Paul D. McNicholas; Sanjeena Subedi (BMC Bioinform., 2019)

On Fractionally-Supervised Classification: Weight Selection and Extension to the Multivariate t-Distribution. - Michael P. B. Gallaugher; Paul D. McNicholas (J. Classif., 2019)

A Mixture of Coalesced Generalized Hyperbolic Distributions. - Cristina Tortora; Brian C. Franczak; Ryan P. Browne; Paul D. McNicholas (J. Classif., 2019)

Editorial for the 4th Special Issue on advances in mixture models. - Jochen Einbeck; John Hinde; Salvatore Ingrassia; Tsung-I Lin; Paul D. McNicholas (Comput. Stat. Data Anal., 2019)

Asymmetric clusters and outliers: Mixtures of multivariate contaminated shifted asymmetric Laplace distributions. - Katherine Morris; Antonio Punzo; Paul D. McNicholas; Ryan P. Browne (Comput. Stat. Data Anal., 2019)

Mixtures of generalized hyperbolic distributions and mixtures of skew-t distributions for model-based clustering with incomplete data. - Yuhong Wei; Yang Tang; Paul D. McNicholas (Comput. Stat. Data Anal., 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. - Paula M. Murray; Ryan P. Browne; Paul D. McNicholas (J. Multivar. Anal., 2019)

Mixtures of skewed matrix variate bilinear factor analyzers. - Michael P. B. Gallaugher; Paul D. McNicholas (Adv. Data Anal. Classif., 2020)

Editorial: Journal of Classification Vol. 37-3. - Paul D. McNicholas (J. Classif., 2020)

Editorial: Journal of Classification Vol. 37-2. - Paul D. McNicholas; Douglas L. Steinley (J. Classif., 2020)

Mixtures of Hidden Truncation Hyperbolic Factor Analyzers. - Paula M. Murray; Ryan P. Browne; Paul D. McNicholas (J. Classif., 2020)

Flexible High-Dimensional Unsupervised Learning with Missing Data. - Yuhong Wei; Yang Tang; Paul D. McNicholas (IEEE Trans. Pattern Anal. Mach. Intell., 2020)

High-dimensional unsupervised classification via parsimonious contaminated mixtures. - Antonio Punzo; Martin Blostein; Paul D. McNicholas (Pattern Recognit., 2020)

A Probabilistic Distance Clustering Algorithm Using Gaussian and Student-t Multivariate Density Distributions. - Cristina Tortora; Paul D. McNicholas; Francesco Palumbo (SN Comput. Sci., 2020)

Clustering discrete-valued time series. - Tyler Roick; Dimitris Karlis; Paul D. McNicholas (Adv. Data Anal. Classif., 2021)

Editorial: Journal of Classification Vol. 38-1. - Paul D. McNicholas (J. Classif., 2021)

Editorial: Journal of Classification Vol. 38-2. - Paul D. McNicholas (J. Classif., 2021)

Editorial: Journal of Classification Vol. 38-3. - Paul D. McNicholas (J. Classif., 2021)

An Evolutionary Algorithm with Crossover and Mutation for Model-Based Clustering. - Sharon M. McNicholas; Paul D. McNicholas; Daniel A. Ashlock (J. Classif., 2021)

A Variational Approximations-DIC Rubric for Parameter Estimation and Mixture Model Selection Within a Family Setting. - Sanjeena Subedi; Paul D. McNicholas (J. Classif., 2021)

Matrix Normal Cluster-Weighted Models. - Salvatore D. Tomarchio; Paul D. McNicholas; Antonio Punzo (J. Classif., 2021)

Model-Based Clustering, Classification, and Discriminant Analysis Using the Generalized Hyperbolic Distribution: MixGHD R package. - Cristina Tortora; Ryan P. Browne; Aisha Elsherbiny; Brian C. Franczak; Paul D. McNicholas (J. Stat. Softw., 2021)

Multivariate cluster weighted models using skewed distributions. - Michael P. B. Gallaugher; Salvatore D. Tomarchio; Paul D. McNicholas; Antonio Punzo (Adv. Data Anal. Classif., 2022)

Correction to: Multivariate cluster weighted models using skewed distributions. - Michael P. B. Gallaugher; Salvatore D. Tomarchio; Paul D. McNicholas; Antonio Punzo (Adv. Data Anal. Classif., 2022)

Editorial: Journal of Classification Vol. 39-1. - Paul D. McNicholas (J. Classif., 2022)

Editorial: Journal of Classification Vol. 39-2. - Paul D. McNicholas (J. Classif., 2022)

Editorial: Journal of Classification Vol. 39-3. - Paul D. McNicholas (J. Classif., 2022)

Mixtures of Matrix-Variate Contaminated Normal Distributions. - Salvatore D. Tomarchio; Michael P. B. Gallaugher; Antonio Punzo; Paul D. McNicholas (J. Comput. Graph. Stat., 2022)

Clustering Three-Way Data with Outliers. - Katharine M. Clark; Paul D. McNicholas (CoRR, 2023)

Model-Based Clustering and Classification Using Mixtures of Multivariate Skewed Power Exponential Distributions. - Utkarsh J. Dang; Michael P. B. Gallaugher; Ryan P. Browne; Paul D. McNicholas (J. Classif., 2023)

Editorial: Journal of Classification Vol. 40-1. - Paul D. McNicholas (J. Classif., 2023)

Finite mixtures of matrix variate Poisson-log normal distributions for three-way count data. - Anjali Silva; Xiaoke Qin; Steven J. Rothstein; Paul D. McNicholas; Sanjeena Subedi (Bioinform., 2023)

Editorial: Journal of Classification Vol. 40-2. - Paul D. McNicholas (J. Classif., 2023)

Parameter-wise co-clustering for high-dimensional data. - Michael P. B. Gallaugher; Christophe Biernacki; Paul D. McNicholas (Comput. Stat., 2023)

Editorial: Journal of Classification Vol. 40-3. - Paul D. McNicholas (J. Classif., 2023)

An EM Gradient Algorithm for Mixture Models with Components Derived from the Manly Transformation. - Katharine M. Clark; Paul D. McNicholas (CoRR, 2024)

Editorial: Journal of Classification Vol. 41-1. - Paul D. McNicholas (J. Classif., 2024)

Finding Outliers in Gaussian Model-based Clustering. - Katharine M. Clark; Paul D. McNicholas (J. Classif., 2024)

Editorial: Journal of Classification Vol. 41-2. - Paul D. McNicholas (J. Classif., 2024)

Editorial: Journal of Classification Vol. 41-3. - Mark de Rooij; Brian C. Franczak; Cinzia Viroli; Arthur White; Paul D. McNicholas (J. Classif., 2024)

Hidden Markov models for multivariate panel data. - Mackenzie R. Neal; Alexa A. Sochaniwsky; Paul D. McNicholas (Stat. Comput., 2024)

Keep It Light! Simplifying Image Clustering Via Text-Free Adapters. - Yicen Li; Haitz Sáez de Ocáriz Borde; Anastasis Kratsios; Paul D. McNicholas (CoRR, 2025)

Editorial: Journal of Classification Vol. 42-1. - Paul D. McNicholas (J. Classif., 2025)

Flexible Clustering with a Sparse Mixture of Generalized Hyperbolic Distributions. - Alexa A. Sochaniwsky; Michael P. B. Gallaugher; Yang Tang; Paul D. McNicholas (J. Classif., 2025)

Depth-Based Local Center Clustering: A Framework for Handling Different Clustering Scenarios. - Siyi Wang; Alexandre Leblanc; Paul D. McNicholas (CoRR, 2025)

Editorial: Journal of Classification Vol. 42-2. - Paul D. McNicholas (J. Classif., 2025)

Unbalanced Longitudinal Data Clustering with a Copula Kernel Mixture Model. - Xi Zhang; Orla A. Murphy; Paul D. McNicholas (Stat. Comput., 2025)