Supervised learning of multivariate skew normal mixture models with missing information
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References listed on IDEAS
- Arellano-Valle, Reinaldo B. & Genton, Marc G., 2005. "On fundamental skew distributions," Journal of Multivariate Analysis, Elsevier, vol. 96(1), pages 93-116, September.
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CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- 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.
- 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.
- 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.
- Loperfido, Nicola, 2014. "Linear transformations to symmetry," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 186-192.
- 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.
More about this item
KeywordsClassifier; EM algorithm; Ignorable; Incomplete data; MSN model; Multivariate truncated normal;
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