default search action
Paul D. McNicholas
Person information
- affiliation: McMaster University, Department of Mathematics and Statistics, Hamilton, Canada
- affiliation: University of Guelph, Canada
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [j83]Paul D. McNicholas:
Editorial: Journal of Classification Vol. 41-1. J. Classif. 41(1): 1 (2024) - [j82]Paul D. McNicholas:
Editorial: Journal of Classification Vol. 41-2. J. Classif. 41(2): 215 (2024) - [j81]Katharine M. Clark, Paul D. McNicholas:
Finding Outliers in Gaussian Model-based Clustering. J. Classif. 41(2): 313-337 (2024) - [j80]Mackenzie R. Neal, Alexa A. Sochaniwsky, Paul D. McNicholas:
Hidden Markov models for multivariate panel data. Stat. Comput. 34(6): 182 (2024) - [i4]Katharine M. Clark, Paul D. McNicholas:
An EM Gradient Algorithm for Mixture Models with Components Derived from the Manly Transformation. CoRR abs/2410.00848 (2024) - 2023
- [j79]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) - [j78]Paul D. McNicholas:
Editorial: Journal of Classification Vol. 40-1. J. Classif. 40(1): 1 (2023) - [j77]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) - [j76]Paul D. McNicholas:
Editorial: Journal of Classification Vol. 40-2. J. Classif. 40(2): 213 (2023) - [j75]Paul D. McNicholas:
Editorial: Journal of Classification Vol. 40-3. J. Classif. 40(3): 467 (2023) - [j74]Michael P. B. Gallaugher, Christophe Biernacki, Paul D. McNicholas:
Parameter-wise co-clustering for high-dimensional data. Comput. Stat. 38(3): 1597-1619 (2023) - [i3]Katharine M. Clark, Paul D. McNicholas:
Clustering Three-Way Data with Outliers. CoRR abs/2310.05288 (2023) - 2022
- [j73]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): 93-124 (2022) - [j72]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): 1097 (2022) - [j71]Paul D. McNicholas:
Editorial: Journal of Classification Vol. 39-1. J. Classif. 39(1): 1-2 (2022) - [j70]Paul D. McNicholas:
Editorial: Journal of Classification Vol. 39-2. J. Classif. 39(2): 217 (2022) - [j69]Paul D. McNicholas:
Editorial: Journal of Classification Vol. 39-3. J. Classif. 39(3): 409 (2022) - [j68]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): 413-421 (2022) - 2021
- [j67]Tyler Roick, Dimitris Karlis, Paul D. McNicholas:
Clustering discrete-valued time series. Adv. Data Anal. Classif. 15(1): 209-229 (2021) - [j66]Paul D. McNicholas:
Editorial: Journal of Classification Vol. 38-1. J. Classif. 38(1): 1 (2021) - [j65]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): 89-108 (2021) - [j64]Paul D. McNicholas:
Editorial: Journal of Classification Vol. 38-2. J. Classif. 38(2): 187 (2021) - [j63]Sharon M. McNicholas, Paul D. McNicholas, Daniel A. Ashlock:
An Evolutionary Algorithm with Crossover and Mutation for Model-Based Clustering. J. Classif. 38(2): 264-279 (2021) - [j62]Paul D. McNicholas:
Editorial: Journal of Classification Vol. 38-3. J. Classif. 38(3): 423-424 (2021) - [j61]Salvatore D. Tomarchio, Paul D. McNicholas, Antonio Punzo:
Matrix Normal Cluster-Weighted Models. J. Classif. 38(3): 556-575 (2021) - [j60]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
- [j59]Michael P. B. Gallaugher, Paul D. McNicholas:
Mixtures of skewed matrix variate bilinear factor analyzers. Adv. Data Anal. Classif. 14(2): 415-434 (2020) - [j58]Paul D. McNicholas, Douglas L. Steinley:
Editorial: Journal of Classification Vol. 37-2. J. Classif. 37(2): 275-276 (2020) - [j57]Paula M. Murray, Ryan P. Browne, Paul D. McNicholas:
Mixtures of Hidden Truncation Hyperbolic Factor Analyzers. J. Classif. 37(2): 366-379 (2020) - [j56]Paul D. McNicholas:
Editorial: Journal of Classification Vol. 37-3. J. Classif. 37(3): 549 (2020) - [j55]Yuhong Wei, Yang Tang, Paul D. McNicholas:
Flexible High-Dimensional Unsupervised Learning with Missing Data. IEEE Trans. Pattern Anal. Mach. Intell. 42(3): 610-621 (2020) - [j54]Antonio Punzo, Martin Blostein, Paul D. McNicholas:
High-dimensional unsupervised classification via parsimonious contaminated mixtures. Pattern Recognit. 98 (2020) - [j53]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): 65 (2020)
2010 – 2019
- 2019
- [j52]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): 394:1-394:11 (2019) - [j51]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) - [j50]Michael P. B. Gallaugher, Paul D. McNicholas:
On Fractionally-Supervised Classification: Weight Selection and Extension to the Multivariate t-Distribution. J. Classif. 36(2): 232-265 (2019) - [j49]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: 18-41 (2019) - [j48]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: 143-144 (2019) - [j47]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) - [j46]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) - 2018
- [j45]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): 823-825 (2018) - [j44]Michael P. B. Gallaugher, Paul D. McNicholas:
Finite mixtures of skewed matrix variate distributions. Pattern Recognit. 80: 83-93 (2018) - [j43]Angelina Pesevski, Brian C. Franczak, Paul D. McNicholas:
Subspace clustering with the multivariate-t distribution. Pattern Recognit. Lett. 112: 297-302 (2018) - [j42]Mateen Shaikh, Paul D. McNicholas, Maria-Luiza Antonie, Thomas Brendan Murphy:
Standardizing interestingness measures for association rules. Stat. Anal. Data Min. 11(6): 282-295 (2018) - [i2]Michael P. B. Gallaugher, Christophe Biernacki, Paul D. McNicholas:
Relaxing the Identically Distributed Assumption in Gaussian Co-Clustering for High Dimensional Data. CoRR abs/1808.08366 (2018) - 2017
- [j41]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): 150:1-150:13 (2017) - [j40]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) - [j39]Antonio Punzo, Paul D. McNicholas:
Robust Clustering in Regression Analysis via the Contaminated Gaussian Cluster-Weighted Model. J. Classif. 34(2): 249-293 (2017) - [j38]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): 46 (2017) - [j37]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
- [j36]Cristina Tortora, Paul D. McNicholas, Ryan P. Browne:
A mixture of generalized hyperbolic factor analyzers. Adv. Data Anal. Classif. 10(4): 423-440 (2016) - [j35]Paul D. McNicholas:
Model-Based Clustering. J. Classif. 33(3): 331-373 (2016) - [j34]John Hinde, Salvatore Ingrassia, Tsung-I Lin, Paul D. McNicholas:
The Third Special Issue on Advances in Mixture Models. Comput. Stat. Data Anal. 93: 2-4 (2016) - [j33]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: 18-30 (2016) - [j32]Amay S. M. Cheam, Paul D. McNicholas:
Modelling receiver operating characteristic curves using Gaussian mixtures. Comput. Stat. Data Anal. 93: 192-208 (2016) - [j31]Katherine Morris, Paul D. McNicholas:
Clustering, classification, discriminant analysis, and dimension reduction via generalized hyperbolic mixtures. Comput. Stat. Data Anal. 97: 133-150 (2016) - 2015
- [j30]Yuhong Wei, Paul D. McNicholas:
Mixture model averaging for clustering. Adv. Data Anal. Classif. 9(2): 197-217 (2015) - [j29]Irene Vrbik, Paul D. McNicholas:
Fractionally-Supervised Classification. J. Classif. 32(3): 359-381 (2015) - [j28]Yang Tang, Ryan P. Browne, Paul D. McNicholas:
Model based clustering of high-dimensional binary data. Comput. Stat. Data Anal. 87: 84-101 (2015) - [j27]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) - [j26]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) - [j25]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): 623-649 (2015) - 2014
- [j24]Sakyajit Bhattacharya, Paul D. McNicholas:
A LASSO-penalized BIC for mixture model selection. Adv. Data Anal. Classif. 8(1): 45-61 (2014) - [j23]Sanjeena Subedi, Paul D. McNicholas:
Variational Bayes approximations for clustering via mixtures of normal inverse Gaussian distributions. Adv. Data Anal. Classif. 8(2): 167-193 (2014) - [j22]Ryan P. Browne, Paul D. McNicholas:
Estimating common principal components in high dimensions. Adv. Data Anal. Classif. 8(2): 217-226 (2014) - [j21]Jeffrey L. Andrews, Paul D. McNicholas:
Variable Selection for Clustering and Classification. J. Classif. 31(2): 136-153 (2014) - [j20]Dankmar Böhning, Christian Hennig, Geoffrey J. McLachlan, Paul D. McNicholas:
The 2nd special issue on advances in mixture models. Comput. Stat. Data Anal. 71: 1-2 (2014) - [j19]Irene Vrbik, Paul D. McNicholas:
Parsimonious skew mixture models for model-based clustering and classification. Comput. Stat. Data Anal. 71: 196-210 (2014) - [j18]Paula M. Murray, Ryan P. Browne, Paul D. McNicholas:
Mixtures of skew-t factor analyzers. Comput. Stat. Data Anal. 77: 326-335 (2014) - [j17]Yu Xia, Paul D. McNicholas:
A gradient method for the monotone fused least absolute shrinkage and selection operator. Optim. Methods Softw. 29(3): 463-483 (2014) - [j16]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) - [j15]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
- [j14]Sanjeena Subedi, Antonio Punzo, Salvatore Ingrassia, Paul D. McNicholas:
Clustering and classification via cluster-weighted factor analyzers. Adv. Data Anal. Classif. 7(1): 5-40 (2013) - [j13]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): 321-338 (2013) - [j12]Jeffrey L. Andrews, Paul D. McNicholas:
Using evolutionary algorithms for model-based clustering. Pattern Recognit. Lett. 34(9): 987-992 (2013) - [j11]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) - [p1]Paul D. McNicholas:
On Clustering and Classification Via Mixtures of Multivariate t-Distributions. Statistical Models for Data Analysis 2013: 233-240 - [i1]Mateen Shaikh, Paul David McNicholas, Maria-Luiza Antonie, Thomas Brendan Murphy:
Standardizing Interestingness Measures for Association Rules. CoRR abs/1308.3740 (2013) - 2012
- [j10]Michelle A. Steane, Paul D. McNicholas, Rickey Y. Yada:
Model-Based Classification via Mixtures of Multivariate t-Factor Analyzers. Commun. Stat. Simul. Comput. 41(4): 510-523 (2012) - [j9]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) - [j8]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): 1021-1029 (2012) - [j7]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): 629-636 (2012) - 2011
- [j6]Jeffrey L. Andrews, Paul D. McNicholas, Sanjeena Subedi:
Model-based classification via mixtures of multivariate t-distributions. Comput. Stat. Data Anal. 55(1): 520-529 (2011) - [j5]Jeffrey L. Andrews, Paul D. McNicholas:
Extending mixtures of multivariate t-factor analyzers. Stat. Comput. 21(3): 361-373 (2011) - [c1]Daniel A. Ashlock, Justin Schonfeld, Paul D. McNicholas:
Translation tables: A genetic code in a evolutionary algorithm. IEEE Congress on Evolutionary Computation 2011: 2685-2692 - 2010
- [j4]Paul David McNicholas, Thomas Brendan Murphy:
Model-based clustering of microarray expression data via latent Gaussian mixture models. Bioinform. 26(21): 2705-2712 (2010) - [j3]Paul David McNicholas, Thomas Brendan Murphy, Aaron F. McDaid, Dermot Frost:
Serial and parallel implementations of model-based clustering via parsimonious Gaussian mixture models. Comput. Stat. Data Anal. 54(3): 711-723 (2010)
2000 – 2009
- 2008
- [j2]Paul David McNicholas, Thomas Brendan Murphy, M. O'Regan:
Standardising the lift of an association rule. Comput. Stat. Data Anal. 52(10): 4712-4721 (2008) - [j1]Paul David McNicholas, Thomas Brendan Murphy:
Parsimonious Gaussian mixture models. Stat. Comput. 18(3): 285-296 (2008)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from , , and to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-12-10 21:43 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint