Two-Stage Leveraged Measurement System Assessment. - Ryan P. Browne; R. Jock MacKay; Stefan H. Steiner (Technometrics, 2009)

Leveraged Gauge R&R Studies. - Ryan P. Browne; R. Jock MacKay; Stefan H. Steiner (Technometrics, 2010)

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)

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)

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

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

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)

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

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)

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)

Subspace clustering for the finite mixture of generalized hyperbolic distributions. - Nam-Hwui Kim; Ryan P. Browne (Adv. Data Anal. Classif., 2019)

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

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

One Line To Rule Them All: Generating LO-Shot Soft-Label Prototypes. - Ilia Sucholutsky; Nam-Hwui Kim; Ryan P. Browne; Matthias Schonlau (IJCNN, 2021)

Functional data clustering by projection into latent generalized hyperbolic subspaces. - Alex Sharp; Ryan P. Browne (Adv. Data Anal. Classif., 2021)

In the pursuit of sparseness: A new rank-preserving penalty for a finite mixture of factor analyzers. - Nam-Hwui Kim; Ryan P. Browne (Comput. Stat. Data Anal., 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)

Factor and hybrid components for model-based clustering. - Jason Hou-Liu; Ryan P. Browne (Adv. Data Anal. Classif., 2022)

On Assessments of Agreement Between Fuzzy Partitions. - Jeffrey L. Andrews; Ryan P. Browne; Chelsey D. Hvingelby (J. Classif., 2022)

Chimeral Clustering. - Jason Hou-Liu; Ryan P. Browne (J. Classif., 2022)

A joint latent factor analyzer and functional subspace model for clustering multivariate functional data. - Alex Sharp; Ryan P. Browne (Stat. Comput., 2022)

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)

Assessing the variability of posterior probabilities in Gaussian model-based clustering. - Yuchi Zhang; Ryan P. Browne; Jeffrey L. Andrews (Commun. Stat. Simul. Comput., 2023)

A dual subspace parsimonious mixture of matrix normal distributions. - Alex Sharp; Glen Chalatov; Ryan P. Browne (Adv. Data Anal. Classif., 2023)

Generalized linear models for massive data via doubly-sketching. - Jason Hou-Liu; Ryan P. Browne (Stat. Comput., 2023)

Flexible mixture regression with the generalized hyperbolic distribution. - Nam-Hwui Kim; Ryan P. Browne (Adv. Data Anal. Classif., 2024)

Model-Based Clustering with Nested Gaussian Clusters. - Jason Hou-Liu; Ryan P. Browne (J. Classif., 2024)

Parsimony and parameter estimation for mixtures of multivariate leptokurtic-normal distributions. - Ryan P. Browne; Luca Bagnato; Antonio Punzo (Adv. Data Anal. Classif., 2024)