mixsmsn

R package mixsmsn: Fitting Finite Mixture of Scale Mixture of Skew-Normal Distributions. Functions to fit finite mixture of scale mixture of skew-normal (FM-SMSN) distributions. (Source: http://cran.r-project.org/web/packages)

Keywords for this software

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References in zbMATH (referenced in 29 articles , 2 standard articles )

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  1. Alexander Foss; Marianthi Markatou: kamila: Clustering Mixed-Type Data in R and Hadoop (2018)
  2. Parisi, Antonio; Liseo, B.: Objective Bayesian analysis for the multivariate skew-t model (2018)
  3. Teimouri, Mahdi; Rezakhah, Saeid; Mohammadpour, Adel: EM algorithm for symmetric stable mixture model (2018)
  4. Zhu, Xuwen; Melnykov, Volodymyr: Manly transformation in finite mixture modeling (2018)
  5. Lachos, Víctor H.; Moreno, Edgar J. López; Chen, Kun; Cabral, Celso R^omulo Barbosa: Finite mixture modeling of censored data using the multivariate Student-$t$ distribution (2017)
  6. Bansal, Naveen K.; Hamedani, Gholamhossein G.; Maadooliat, Mehdi: Testing multiple hypotheses with skewed alternatives (2016)
  7. 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)
  8. Li, Huiqiong; Wu, Liucang; Yi, Jieyi: A skew-normal mixture of joint location, scale and skewness models (2016)
  9. O’Hagan, Adrian; Murphy, Thomas Brendan; Gormley, Isobel Claire; McNicholas, Paul D.; Karlis, Dimitris: Clustering with the multivariate normal inverse Gaussian distribution (2016)
  10. Zeller, Camila B.; Cabral, Celso R. B.; Lachos, Víctor H.: Robust mixture regression modeling based on scale mixtures of skew-normal distributions (2016)
  11. Browne, Ryan P.; McNicholas, Paul D.: A mixture of generalized hyperbolic distributions (2015)
  12. Sharon X. Lee, Geoffrey J. McLachlan: EMMIXcskew: an R Package for the Fitting of a Mixture of Canonical Fundamental Skew t-Distributions (2015) arXiv
  13. Tarpey, Thaddeus; Loperfido, Nicola: Self-consistency and a generalized principal subspace theorem (2015)
  14. Cabral, Celso R^omulo Barbosa; Lachos, Víctor Hugo; Zeller, Camila Borelli: Multivariate measurement error models using finite mixtures of skew-Student $t$ distributions (2014)
  15. Lee, Sharon; McLachlan, Geoffrey J.: Finite mixtures of multivariate skew $t$-distributions: some recent and new results (2014)
  16. Lin, Tsung-I; Ho, Hsiu J.; Lee, Chia-Rong: Flexible mixture modelling using the multivariate skew-$t$-normal distribution (2014)
  17. Menardi, Giovanna; Azzalini, Adelchi: An advancement in clustering via nonparametric density estimation (2014)
  18. Ahmad, Ola Suleiman; Pinoli, Jean-Charles: Lipschitz-Killing curvatures of the excursion sets of skew Student’s $t$ random fields (2013)
  19. Galimberti, Giuliano; Montanari, Angela: Discussion of “Model-based clustering and classification with non-normal mixture distributions” by S. X. Lee and G. J. McLachlan (2013)
  20. García-Escudero, L. A.; Gordaliza, A.; Mayo-Iscar, A.: Comments on: “Model-based clustering and classification with non-normal mixture distributions” (2013)

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