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Supervised learning of multivariate skew normal mixture models with missing information


  • Tzy-Chy Lin
  • Tsung-I Lin



No abstract is available for this item.

Suggested Citation

  • Tzy-Chy Lin & Tsung-I Lin, 2010. "Supervised learning of multivariate skew normal mixture models with missing information," Computational Statistics, Springer, vol. 25(2), pages 183-201, June.
  • Handle: RePEc:spr:compst:v:25:y:2010:i:2:p:183-201
    DOI: 10.1007/s00180-009-0169-5

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    References listed on IDEAS

    1. Reinaldo B. Arellano-Valle & Adelchi Azzalini, 2006. "On the Unification of Families of Skew-normal Distributions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(3), pages 561-574.
    2. Di Zio, Marco & Guarnera, Ugo & Luzi, Orietta, 2007. "Imputation through finite Gaussian mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5305-5316, July.
    3. Arellano-Valle, Reinaldo B. & Genton, Marc G., 2005. "On fundamental skew distributions," Journal of Multivariate Analysis, Elsevier, vol. 96(1), pages 93-116, September.
    4. R.B. Arellano-Valle & H. Bolfarine & V.H. Lachos, 2007. "Bayesian Inference for Skew-normal Linear Mixed Models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(6), pages 663-682.
    5. Tsung-I Lin & Hsiu Ho & Pao Shen, 2009. "Computationally efficient learning of multivariate t mixture models with missing information," Computational Statistics, Springer, vol. 24(3), pages 375-392, August.
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    Cited by:

    1. Camila B. Zeller & Celso R. B. Cabral & Víctor H. Lachos, 2016. "Robust mixture regression modeling based on scale mixtures of skew-normal distributions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(2), pages 375-396, June.
    2. Wan-Lun Wang & Tsung-I Lin, 2013. "An efficient ECM algorithm for maximum likelihood estimation in mixtures of t-factor analyzers," Computational Statistics, Springer, vol. 28(2), pages 751-769, April.
    3. Hea-Jung Kim, 2015. "A best linear threshold classification with scale mixture of skew normal populations," Computational Statistics, Springer, vol. 30(1), pages 1-28, March.
    4. Loperfido, Nicola, 2014. "A note on the fourth cumulant of a finite mixture distribution," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 386-394.
    5. Loperfido, Nicola, 2014. "Linear transformations to symmetry," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 186-192.


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