R package mclust: Normal Mixture Modeling for Model-Based Clustering, Classification, and Density Estimation , Normal Mixture Modeling fitted via EM algorithm for Model-Based Clustering, Classification, and Density Estimation, including Bayesian regularization.

References in zbMATH (referenced in 304 articles , 2 standard articles )

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  1. Anderlucci, Laura; Fortunato, Francesca; Montanari, Angela: High-dimensional clustering via random projections (2022)
  2. Diani, Cecilia; Galimberti, Giuliano; Soffritti, Gabriele: Multivariate cluster-weighted models based on seemingly unrelated linear regression (2022)
  3. García-Escudero, Luis A.; Mayo-Iscar, Agustín; Riani, Marco: Constrained parsimonious model-based clustering (2022)
  4. Hou-Liu, Jason; Browne, Ryan P.: Chimeral clustering (2022)
  5. Scaldelai, D.; Matioli, L. C.; Santos, S. R.; Kleina, M.: MulticlusterKDE: a new algorithm for clustering based on multivariate kernel density estimation (2022)
  6. Wang, Wan-Lun; Lin, Tsung-I: Robust clustering of multiply censored data via mixtures of (t) factor analyzers (2022)
  7. Youjiao Yu: mixR: An R package for Finite Mixture Modeling for Both Raw and Binned Data (2022) not zbMATH
  8. Batool, Fatima; Hennig, Christian: Clustering with the average silhouette width (2021)
  9. Biernacki, Christophe; Marbac, Matthieu; Vandewalle, Vincent: Gaussian-based visualization of Gaussian and non-Gaussian-based clustering (2021)
  10. Braverman, Amy; Hobbs, Jonathan; Teixeira, Joaquim; Gunson, Michael: Post hoc uncertainty quantification for remote sensing observing systems (2021)
  11. Cappozzo, Andrea; Greselin, Francesca; Murphy, Thomas Brendan: Robust variable selection for model-based learning in presence of adulteration (2021)
  12. Carel, Léna; Alquier, Pierre: Simultaneous dimension reduction and clustering via the NMF-EM algorithm (2021)
  13. Casa, Alessandro; Scrucca, Luca; Menardi, Giovanna: Better than the best? Answers via model ensemble in density-based clustering (2021)
  14. 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
  15. Jouvin, Nicolas; Bouveyron, Charles; Latouche, Pierre: A Bayesian Fisher-EM algorithm for discriminative Gaussian subspace clustering (2021)
  16. Jung, Sungkyu; Park, Kiho; Kim, Byungwon: Clustering on the torus by conformal prediction (2021)
  17. Kim, Nam-Hwui; Browne, Ryan P.: In the pursuit of sparseness: a new rank-preserving penalty for a finite mixture of factor analyzers (2021)
  18. Lim, David K.; Rashid, Naim U.; Ibrahim, Joseph G.: Model-based feature selection and clustering of RNA-seq data for unsupervised subtype discovery (2021)
  19. Manole, Tudor; Khalili, Abbas: Estimating the number of components in finite mixture models via the group-sort-fuse procedure (2021)
  20. McNicholas, Sharon M.; McNicholas, Paul D.; Ashlock, Daniel A.: An evolutionary algorithm with crossover and mutation for model-based clustering (2021)

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