References in zbMATH (referenced in 75 articles )

Showing results 1 to 20 of 75.
Sorted by year (citations)

1 2 3 4 next

  1. 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 (2021) not zbMATH
  2. Kim, Nam-Hwui; Browne, Ryan P.: In the pursuit of sparseness: a new rank-preserving penalty for a finite mixture of factor analyzers (2021)
  3. Lu, Xiang; Li, Yaoxiang; Love, Tanzy: On Bayesian analysis of parsimonious Gaussian mixture models (2021)
  4. Almodóvar-Rivera, Israel A.; Maitra, Ranjan: Kernel-estimated nonparametric overlap-based syncytial clustering (2020)
  5. Giordani, Paolo; Ferraro, Maria Brigida; Martella, Francesca: An introduction to clustering with R (2020)
  6. Murphy, Keefe; Viroli, Cinzia; Gormley, Isobel Claire: Infinite mixtures of infinite factor analysers (2020)
  7. Papastamoulis, Panagiotis: Clustering multivariate data using factor analytic Bayesian mixtures with an unknown number of components (2020)
  8. Cappozzo, Andrea; Greselin, Francesca: Detecting wine adulterations employing robust mixture of factor analyzers (2019)
  9. Kim, Nam-Hwui; Browne, Ryan: Subspace clustering for the finite mixture of generalized hyperbolic distributions (2019)
  10. Marbac, Matthieu; Vandewalle, Vincent: A tractable multi-partitions clustering (2019)
  11. Scrucca, Luca; Serafini, Alessio: Projection pursuit based on Gaussian mixtures and evolutionary algorithms (2019)
  12. Cerioli, Andrea; García-Escudero, Luis Angel; Mayo-Iscar, Agustín; Riani, Marco: Finding the number of normal groups in model-based clustering via constrained likelihoods (2018)
  13. Fop, Michael; Murphy, Thomas Brendan: Variable selection methods for model-based clustering (2018)
  14. Galimberti, Giuliano; Manisi, Annamaria; Soffritti, Gabriele: Modelling the role of variables in model-based cluster analysis (2018)
  15. Luca Scrucca; Adrian Raftery: clustvarsel: A Package Implementing Variable Selection for Gaussian Model-Based Clustering in R (2018) not zbMATH
  16. Papastamoulis, Panagiotis: Overfitting Bayesian mixtures of factor analyzers with an unknown number of components (2018)
  17. Wallace, Meredith L.; Buysse, Daniel J.; Germain, Anne; Hall, Martica H.; Iyengar, Satish: Variable selection for skewed model-based clustering: application to the identification of novel sleep phenotypes (2018)
  18. Dang, Utkarsh J.; Punzo, Antonio; McNicholas, Paul D.; Ingrassia, Salvatore; Browne, Ryan P.: Multivariate response and parsimony for Gaussian cluster-weighted models (2017)
  19. Hui, Francis K. C.: Model-based simultaneous clustering and ordination of multivariate abundance data in ecology (2017)
  20. Murray, Paula M.; Browne, Ryan P.; McNicholas, Paul D.: Hidden truncation hyperbolic distributions, finite mixtures thereof, and their application for clustering (2017)

1 2 3 4 next