References in zbMATH (referenced in 48 articles )

Showing results 1 to 20 of 48.
Sorted by year (citations)

1 2 3 next

  1. Dang, Utkarsh J.; Punzo, Antonio; McNicholas, Paul D.; Ingrassia, Salvatore; Browne, Ryan P.: Multivariate response and parsimony for Gaussian cluster-weighted models (2017)
  2. Murray, Paula M.; Browne, Ryan P.; McNicholas, Paul D.: Hidden truncation hyperbolic distributions, finite mixtures thereof, and their application for clustering (2017)
  3. Naderi, Mehrdad; Arabpour, Alireza; Lin, Tsung-I; Jamalizadeh, Ahad: Nonlinear regression models based on the normal mean-variance mixture of Birnbaum-Saunders distribution (2017)
  4. Punzo, Antonio; McNicholas, Paul.D.: Robust clustering in regression analysis via the contaminated Gaussian cluster-weighted model (2017)
  5. Antonio Punzo, Angelo Mazza, Paul D. McNicholas: ContaminatedMixt: An R Package for Fitting Parsimonious Mixtures of Multivariate Contaminated Normal Distributions (2016) arXiv
  6. Berta, Paolo; Ingrassia, Salvatore; Punzo, Antonio; Vittadini, Giorgio: Multilevel cluster-weighted models for the evaluation of hospitals (2016)
  7. Galimberti, Giuliano; Scardovi, Elena; Soffritti, Gabriele: Using mixtures in seemingly unrelated linear regression models with non-normal errors (2016)
  8. Kosmidis, Ioannis; Karlis, Dimitris: Model-based clustering using copulas with applications (2016)
  9. Lee, Sharon X.; McLachlan, Geoffrey J.: Finite mixtures of canonical fundamental skew $t$-distributions. The unification of the restricted and unrestricted skew $t$-mixture models (2016)
  10. Lin, Tsung-I; McLachlan, Geoffrey J.; Lee, Sharon X.: Extending mixtures of factor models using the restricted multivariate skew-normal distribution (2016)
  11. Malsiner-Walli, Gertraud; Frühwirth-Schnatter, Sylvia; Grün, Bettina: Model-based clustering based on sparse finite Gaussian mixtures (2016)
  12. McNicholas, Paul D.: Model-based clustering (2016)
  13. Bouveyron, C.; Fauvel, M.; Girard, S.: Kernel discriminant analysis and clustering with parsimonious Gaussian process models (2015)
  14. Greselin, Francesca; Ingrassia, Salvatore: Maximum likelihood estimation in constrained parameter spaces for mixtures of factor analyzers (2015)
  15. Ingrassia, Salvatore; Punzo, Antonio; Vittadini, Giorgio; Minotti, Simona C.: The generalized linear mixed cluster-weighted model (2015)
  16. Ingrassia, Salvatore; Punzo, Antonio; Vittadini, Giorgio; Minotti, Simona C.: Erratum to: “The generalized linear mixed cluster-weighted model” (2015)
  17. Lin, Tsung-I; Wu, Pal H.; McLachlan, Geoffrey J.; Lee, Sharon X.: A robust factor analysis model using the restricted skew-$t$ distribution (2015)
  18. Sylla, Seydou N.; Girard, Stéphane; Diongue, Abdou Ka; Diallo, Aldiouma; Sokhna, Cheikh: A classification method for binary predictors combining similarity measures and mixture models (2015)
  19. Andrews, Jeffrey L.; McNicholas, Paul D.: Variable selection for clustering and classification (2014)
  20. Biernacki, Christophe; Lourme, Alexandre: Stable and visualizable Gaussian parsimonious clustering models (2014)

1 2 3 next