R. Browne

发表

Multivariate Response and Parsimony for Gaussian Cluster-Weighted Models

Ryan P. Browne, P. McNicholas, S. Ingrassia, 2017, Journal of Classification.

A parsimonious family of multivariate Poisson-lognormal distributions for clustering multivariate count data

Ryan P. Browne, S. Subedi, Sanjeena Subedi, 2020, 2004.06857.

A family of parsimonious mixtures of multivariate Poisson‐lognormal distributions for clustering multivariate count data

Ryan P. Browne, S. Subedi, Sanjeena Subedi, 2020, Stat.

Model-Based Learning Using a Mixture of Mixtures of Gaussian and Uniform Distributions

Ryan P. Browne, Paul D. McNicholas, Matthew D. Sparling, 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A dual subspace parsimonious mixture of matrix normal distributions

Ryan P. Browne, A. Sharp, Glen Chalatov, 2022, Advances in Data Analysis and Classification.

Multivariate Response and Parsimony for Gaussian Cluster-Weighted Models

Ryan P. Browne, Paul D. McNicholas, Utkarsh J. Dang, 2014, Journal of Classification.

A Mixture of Coalesced Generalized Hyperbolic Distributions

Ryan P. Browne, P. McNicholas, B. Franczak, 2014, J. Classif..

Mixtures of Multiple Scaled Generalized Hyperbolic Distributions

Ryan P. Browne, Paul D. McNicholas, Cristina Tortora, 2014 .

On nomenclature for, and the relative merits of, two formulations of skew distributions

Ryan P. Browne, P. McNicholas, M. Genton, 2014, 1402.5431.

A mixture of generalized hyperbolic factor analyzers

Ryan P. Browne, Paul D. McNicholas, Cristina Tortora, 2013, Advances in Data Analysis and Classification.

A mixture of SDB skew-t factor analyzers

Ryan P. Browne, Paul D. McNicholas, Paula M. Murray, 2013, 1310.6224.

A mixture of generalized hyperbolic distributions

Ryan P. Browne, P. McNicholas, R. Browne, 2013, 1305.1036.

Mixtures of Shifted AsymmetricLaplace Distributions

Ryan P. Browne, Paul D. McNicholas, Brian C. Franczak, 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Chimeral Clustering

Ryan P. Browne, Jason Hou-Liu, R. Browne, 2021, J. Classif..

Chimeral Clustering

Ryan P. Browne, Jason Hou-Liu, R. Browne, 2021, Journal of Classification.

A joint latent factor analyzer and functional subspace model for clustering multivariate functional data

Ryan P. Browne, Alex Sharp, R. Browne, 2022, Statistics and Computing.

Functional data clustering by projection into latent generalized hyperbolic subspaces

Alex Sharp, Ryan Browne, A. Sharp, 2021, Advances in Data Analysis and Classification.

Functional data clustering by projection into latent generalized hyperbolic subspaces

A. Sharp, R. Browne, 2021, Advances in Data Analysis and Classification.

Subspace clustering for the finite mixture of generalized hyperbolic distributions

Ryan P. Browne, Nam-Hwui Kim, Nam-Hwui Kim, 2018, Adv. Data Anal. Classif..

One Line To Rule Them All: Generating LO-Shot Soft-Label Prototypes

Ryan P. Browne, Matthias Schonlau, Ilia Sucholutsky, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

Anderson relaxation test for intrinsic dimension selection in model-based clustering

Ryan P. Browne, Nam-Hwui Kim, R. Browne, 2022, Journal of Statistical Computation and Simulation.

Mixtures of Hidden Truncation Hyperbolic Factor Analyzers

Ryan P. Browne, P. McNicholas, P. Murray, 2019, Journal of Classification.

A Mixture of Coalesced Generalized Hyperbolic Distributions

Ryan P. Browne, P. McNicholas, B. Franczak, 2019, Journal of Classification.

Mixtures of Hidden Truncation Hyperbolic Factor Analyzers

Ryan P. Browne, Paul D. McNicholas, Paula M. Murray, 2017, J. Classif..

Hidden truncation hyperbolic distributions, finite mixtures thereof, and their application for clustering

Ryan P. Browne, Paul D. McNicholas, Paula M. Murray, 2017, J. Multivar. Anal..

A mixture of generalized hyperbolic factor analyzers

Ryan P. Browne, P. McNicholas, C. Tortora, 2015, Advances in Data Analysis and Classification.

Model-Based Clustering Using Mixtures of Coalesced Generalized Hyperbolic Distributions

Ryan P. Browne, Paul D. McNicholas, Cristina Tortora, 2014 .

Asymmetric clusters and outliers: Mixtures of multivariate contaminated shifted asymmetric Laplace distributions

Ryan P. Browne, Paul D. McNicholas, Antonio Punzo, 2014, Comput. Stat. Data Anal..

Robust Asymmetric Clustering

Ryan P. Browne, P. McNicholas, A. Punzo, 2014 .

Comparing two formulations of skew distributions with special reference to model-based clustering

Ryan P. Browne, Paul D. McNicholas, Marc G. Genton, 2014 .

Mixtures of Variance-Gamma Distributions

Ryan P. Browne, Paul D. McNicholas, Sharon M. McNicholas, 2013, 1309.2695.

A mixture of common skew‐t factor analysers

Ryan P. Browne, Paul D. McNicholas, Paula M. Murray, 2013, 1307.5558.

Mixtures of skew-t factor analyzers

Ryan P. Browne, Paul D. McNicholas, Paula M. Murray, 2013, Comput. Stat. Data Anal..

M E ] 2 7 O ct 2 01 8 Mixtures of Hidden Truncation Hyperbolic Factor Analyzers

P. McNicholas, P. Murray, R. Browne, 2018 .

A Mixture of Variance-Gamma Factor Analyzers

P. McNicholas, S. McNicholas, R. Browne, 2017 .

Mixtures of Shifted Asymmetric Laplace Distributions

Ryan P. Browne, P. McNicholas, B. Franczak, 2012 .

Optimal two‐stage reliability studies

Ryan P. Browne, R. J. MacKay, S. Steiner, 2010, Statistics in medicine.

Mixtures of multivariate power exponential distributions

Ryan P. Browne, P. McNicholas, U. Dang, 2015, Biometrics.

Model-Based Clustering, Classification, and Discriminant Analysis Using the Generalized Hyperbolic Distribution: MixGHD R package

Ryan P. Browne, Paul D. McNicholas, Cristina Tortora, 2021, J. Stat. Softw..

Statistical inference for sketching algorithms

R. Browne, J. Andrews, 2023, 2306.03593.

Flexible mixture regression with the generalized hyperbolic distribution

Ryan P. Browne, Nam-Hwui Kim, R. Browne, 2023, Advances in Data Analysis and Classification.

Assessing the variability of posterior probabilities in Gaussian model-based clustering

Ryan P. Browne, Jeffrey L. Andrews, Yuchi Zhang, 2021, Commun. Stat. Simul. Comput..

Hypothesis Testing for Mixture Model Selection

Ryan P. Browne, P. McNicholas, A. Punzo, 2016 .

Unsupervised learning via mixtures of skewed distributions with hypercube contours

Ryan P. Browne, Paul D. McNicholas, Cristina Tortora, 2014, Pattern Recognit. Lett..

Model-based clustering, classification, and discriminant analysis of data with mixed type

Ryan P. Browne, Paul D. McNicholas, P. McNicholas, 2012 .

Subspace clustering for the finite mixture of generalized hyperbolic distributions

Nam-Hwui Kim, R. Browne, 2018, Advances in Data Analysis and Classification.

Generalized linear models for massive data via doubly-sketching

Jason Hou-Liu, R. Browne, 2023, Statistics and Computing.

Discussion of ‘Model-based clustering and classification with non-normal mixture distributions’ by Lee and McLachlan

P. McNicholas, P. Murray, R. Browne, 2013, Statistical Methods & Applications.

Discussion of ‘Model-based clustering and classification with non-normal mixture distributions’ by Lee and McLachlan

Ryan P. Browne, Paul D. McNicholas, Paula M. Murray, 2013, Stat. Methods Appl..

Hypothesis Testing for Parsimonious Gaussian Mixture Models

Ryan P. Browne, P. McNicholas, A. Punzo, 2014, 1405.0377.

Model based clustering of high-dimensional binary data

Yang Tang, Ryan P. Browne, Paul D. McNicholas, 2014, Comput. Stat. Data Anal..

Factor and hybrid components for model-based clustering

Ryan P. Browne, Jason Hou-Liu, R. Browne, 2022, Adv. Data Anal. Classif..

Factor and hybrid components for model-based clustering

Ryan P. Browne, Jason Hou-Liu, R. Browne, 2022, Advances in Data Analysis and Classification.

Flexible clustering of high‐dimensional data via mixtures of joint generalized hyperbolic distributions

Ryan P. Browne, Paul D. McNicholas, Yang Tang, 2017, 1705.03130.

A partial EM algorithm for model‐based clustering with highly diverse missing data patterns

Ryan P. Browne, P. McNicholas, C. Findlay, 2021, Stat.

Mixtures of Skewed Hypercubes

Ryan P. Browne, P. McNicholas, B. Franczak, 2014 .

Parsimonious Shifted Asymmetric Laplace Mixtures

Ryan P. Browne, P. McNicholas, P. Murray, 2013, 1311.0317.

Mixtures of 'Unrestricted' Skew-t Factor Analyzers

Ryan P. Browne, Paul D. McNicholas, Paula M. Murray, 2013 .

A Partial EM Algorithm for Clustering White Breads

P. McNicholas, C. Findlay, R. Browne, 2013, 1302.6625.

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

Ryan P. Browne, Paul D. McNicholas, Paula M. Murray, 2019, J. Multivar. Anal..

Assessment of a Measurement System Using Repeat Measurements of Failing Units

Ryan P. Browne, R. Browne, 2009 .

Leveraged Gauge R&R Studies

Stefan H. Steiner, Ryan P. Browne, R. Jock MacKay, 2010, Technometrics.

In the pursuit of sparseness: A new rank-preserving penalty for a finite mixture of factor analyzers

Ryan P. Browne, Nam-Hwui Kim, Nam-Hwui Kim, 2021, Comput. Stat. Data Anal..

Product selection for liking studies: The sensory informed design

Ryan P. Browne, Paul D. McNicholas, Christopher J. Findlay, 2015 .

Estimating common principal components in high dimensions

P. McNicholas, R. Browne, 2013, Advances in Data Analysis and Classification.

Estimating common principal components in high dimensions

Ryan P. Browne, Paul D. McNicholas, P. McNicholas, 2013, Advances in Data Analysis and Classification.

Orthogonal Stiefel manifold optimization for eigen-decomposed covariance parameter estimation in mixture models

Ryan P. Browne, Paul D. McNicholas, P. McNicholas, 2012, Statistics and Computing.

Planning and analysis of measurement reliability studies

Ryan P. Browne, Nathaniel T. Stevens, R. J. MacKay, 2011 .

Multivariate sharp quadratic bounds via $\mathbf{\Sigma}$-strong convexity and the Fenchel connection

Ryan P. Browne, P. McNicholas, R. Browne, 2015 .

Mode merging for the finite mixture of t‐distributions

Nam-Hwui Kim, R. Browne, 2021, Stat.

Improved Measurement-System Assessment for Processes with 100% Inspection

Stefan H. Steiner, Ryan P. Browne, R. Jock MacKay, 2009 .

Handling missing data in consumer hedonic tests arising from direct scaling

Ryan P. Browne, P. McNicholas, J. C. Castura, 2016 .