mixture

R package mixture: Mixture Models for Clustering and Classification. An implementation of all 14 Gaussian parsimonious clustering models (GPCMs) for model-based clustering and model-based classification.

Keywords for this software

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References in zbMATH (referenced in 31 articles )

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  1. García-Escudero, Luis A.; Mayo-Iscar, Agustín; Riani, Marco: Constrained parsimonious model-based clustering (2022)
  2. Lee, Sharon X.; McLachlan, Geoffrey J.: An overview of skew distributions in model-based clustering (2022)
  3. 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
  4. Kim, Nam-Hwui; Browne, Ryan P.: In the pursuit of sparseness: a new rank-preserving penalty for a finite mixture of factor analyzers (2021)
  5. Lee, Sharon X.; Lin, Tsung-I.; McLachlan, Geoffrey J.: Mixtures of factor analyzers with scale mixtures of fundamental skew normal distributions (2021)
  6. McNicholas, Sharon M.; McNicholas, Paul D.; Ashlock, Daniel A.: An evolutionary algorithm with crossover and mutation for model-based clustering (2021)
  7. Punzo, Antonio; Tortora, Cristina: Multiple scaled contaminated normal distribution and its application in clustering (2021)
  8. Almodóvar-Rivera, Israel A.; Maitra, Ranjan: Kernel-estimated nonparametric overlap-based syncytial clustering (2020)
  9. Giordani, Paolo; Ferraro, Maria Brigida; Martella, Francesca: An introduction to clustering with R (2020)
  10. Paindaveine, Davy; Remy, Julien; Verdebout, Thomas: Sign tests for weak principal directions (2020)
  11. Paindaveine, Davy; Remy, Julien; Verdebout, Thomas: Testing for principal component directions under weak identifiability (2020)
  12. Gallaugher, Michael P. B.; McNicholas, Paul D.: On fractionally-supervised classification: weight selection and extension to the multivariate (t)-distribution (2019)
  13. Rainey, Christopher; Tortora, Cristina; Palumbo, Francesco: A parametric version of probabilistic distance clustering (2019)
  14. Tortora, Cristina; Franczak, Brian C.; Browne, Ryan P.; McNicholas, Paul D.: A mixture of coalesced generalized hyperbolic distributions (2019)
  15. Alexander Foss; Marianthi Markatou: kamila: Clustering Mixed-Type Data in R and Hadoop (2018) not zbMATH
  16. Galimberti, Giuliano; Manisi, Annamaria; Soffritti, Gabriele: Modelling the role of variables in model-based cluster analysis (2018)
  17. Jeffrey Andrews; Jaymeson Wickins; Nicholas Boers; Paul McNicholas: teigen: An R Package for Model-Based Clustering and Classification via the Multivariate t Distribution (2018) not zbMATH
  18. 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)
  19. Dang, Utkarsh J.; Punzo, Antonio; McNicholas, Paul D.; Ingrassia, Salvatore; Browne, Ryan P.: Multivariate response and parsimony for Gaussian cluster-weighted models (2017)
  20. Antonio Punzo, Angelo Mazza, Paul D. McNicholas: ContaminatedMixt: An R Package for Fitting Parsimonious Mixtures of Multivariate Contaminated Normal Distributions (2016) arXiv

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