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Ryan P. Browne
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Journal Articles
- 2024
- [j33]Nam-Hwui Kim, Ryan P. Browne:
Flexible mixture regression with the generalized hyperbolic distribution. Adv. Data Anal. Classif. 18(1): 33-60 (2024) - [j32]Ryan P. Browne, Luca Bagnato, Antonio Punzo:
Parsimony and parameter estimation for mixtures of multivariate leptokurtic-normal distributions. Adv. Data Anal. Classif. 18(3): 597-625 (2024) - [j31]Jason Hou-Liu, Ryan P. Browne:
Model-Based Clustering with Nested Gaussian Clusters. J. Classif. 41(1): 39-64 (2024) - 2023
- [j30]Alex Sharp, Glen Chalatov, Ryan P. Browne:
A dual subspace parsimonious mixture of matrix normal distributions. Adv. Data Anal. Classif. 17(3): 801-822 (2023) - [j29]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): 145-167 (2023) - [j28]Yuchi Zhang, Ryan P. Browne, Jeffrey L. Andrews:
Assessing the variability of posterior probabilities in Gaussian model-based clustering. Commun. Stat. Simul. Comput. 52(5): 1937-1947 (2023) - [j27]Jason Hou-Liu, Ryan P. Browne:
Generalized linear models for massive data via doubly-sketching. Stat. Comput. 33(5): 105 (2023) - 2022
- [j26]Jason Hou-Liu, Ryan P. Browne:
Factor and hybrid components for model-based clustering. Adv. Data Anal. Classif. 16(2): 373-398 (2022) - [j25]Jason Hou-Liu, Ryan P. Browne:
Chimeral Clustering. J. Classif. 39(1): 171-190 (2022) - [j24]Jeffrey L. Andrews, Ryan P. Browne, Chelsey D. Hvingelby:
On Assessments of Agreement Between Fuzzy Partitions. J. Classif. 39(2): 326-342 (2022) - [j23]Alex Sharp, Ryan P. Browne:
A joint latent factor analyzer and functional subspace model for clustering multivariate functional data. Stat. Comput. 32(5): 68 (2022) - 2021
- [j22]Alex Sharp, Ryan P. Browne:
Functional data clustering by projection into latent generalized hyperbolic subspaces. Adv. Data Anal. Classif. 15(3): 735-757 (2021) - [j21]Nam-Hwui Kim, Ryan P. Browne:
In the pursuit of sparseness: A new rank-preserving penalty for a finite mixture of factor analyzers. Comput. Stat. Data Anal. 160: 107244 (2021) - [j20]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) - 2020
- [j19]Paula M. Murray, Ryan P. Browne, Paul D. McNicholas:
Mixtures of Hidden Truncation Hyperbolic Factor Analyzers. J. Classif. 37(2): 366-379 (2020) - 2019
- [j18]Nam-Hwui Kim, Ryan P. Browne:
Subspace clustering for the finite mixture of generalized hyperbolic distributions. Adv. Data Anal. Classif. 13(3): 641-661 (2019) - [j17]Cristina Tortora, Brian C. Franczak, Ryan P. Browne, Paul D. McNicholas:
A Mixture of Coalesced Generalized Hyperbolic Distributions. J. Classif. 36(1): 26-57 (2019) - [j16]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: 145-166 (2019) - [j15]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: 475-476 (2019) - 2017
- [j14]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): 4-34 (2017) - [j13]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: 141-156 (2017) - 2016
- [j12]Cristina Tortora, Paul D. McNicholas, Ryan P. Browne:
A mixture of generalized hyperbolic factor analyzers. Adv. Data Anal. Classif. 10(4): 423-440 (2016) - 2015
- [j11]Yang Tang, Ryan P. Browne, Paul D. McNicholas:
Model based clustering of high-dimensional binary data. Comput. Stat. Data Anal. 87: 84-101 (2015) - [j10]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: 69-76 (2015) - [j9]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: 68 (2015) - 2014
- [j8]Ryan P. Browne, Paul D. McNicholas:
Estimating common principal components in high dimensions. Adv. Data Anal. Classif. 8(2): 217-226 (2014) - [j7]Paula M. Murray, Ryan P. Browne, Paul D. McNicholas:
Mixtures of skew-t factor analyzers. Comput. Stat. Data Anal. 77: 326-335 (2014) - [j6]Brian C. Franczak, Ryan P. Browne, Paul D. McNicholas:
Mixtures of Shifted AsymmetricLaplace Distributions. IEEE Trans. Pattern Anal. Mach. Intell. 36(6): 1149-1157 (2014) - [j5]Ryan P. Browne, Paul D. McNicholas:
Orthogonal Stiefel manifold optimization for eigen-decomposed covariance parameter estimation in mixture models. Stat. Comput. 24(2): 203-210 (2014) - 2013
- [j4]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): 467-472 (2013) - 2012
- [j3]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): 814-817 (2012) - 2010
- [j2]Ryan P. Browne, R. Jock MacKay, Stefan H. Steiner:
Leveraged Gauge R&R Studies. Technometrics 52(3): 294-302 (2010) - 2009
- [j1]Ryan P. Browne, R. Jock MacKay, Stefan H. Steiner:
Two-Stage Leveraged Measurement System Assessment. Technometrics 51(3): 239-249 (2009)
Conference and Workshop Papers
- 2021
- [c1]Ilia Sucholutsky, Nam-Hwui Kim, Ryan P. Browne, Matthias Schonlau:
One Line To Rule Them All: Generating LO-Shot Soft-Label Prototypes. IJCNN 2021: 1-8
Informal and Other Publications
- 2021
- [i1]Ilia Sucholutsky, Nam-Hwui Kim, Ryan P. Browne, Matthias Schonlau:
One Line To Rule Them All: Generating LO-Shot Soft-Label Prototypes. CoRR abs/2102.07834 (2021)
Coauthor Index
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last updated on 2024-12-10 21:48 CET by the dblp team
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