Dimensionally Reduced Model-Based Clustering Through Mixtures of Factor Mixture Analyzers
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References listed on IDEAS
- McLachlan, G. J. & Peel, D. & Bean, R. W., 2003. "Modelling high-dimensional data by mixtures of factor analyzers," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 379-388, January.
- Chris Fraley & Adrian E. Raftery, 2007. "Bayesian Regularization for Normal Mixture Estimation and Model-Based Clustering," Journal of Classification, Springer;The Classification Society, vol. 24(2), pages 155-181, September.
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- Paul D. McNicholas, 2016. "Model-Based Clustering," Journal of Classification, Springer;The Classification Society, vol. 33(3), pages 331-373, October.
- Jeffrey Andrews & Paul McNicholas, 2014. "Variable Selection for Clustering and Classification," Journal of Classification, Springer;The Classification Society, vol. 31(2), pages 136-153, July.
- Wang, Wan-Lun, 2015. "Mixtures of common t-factor analyzers for modeling high-dimensional data with missing values," Computational Statistics & Data Analysis, Elsevier, vol. 83(C), pages 223-235.
- Dvorkin Daniel & Biehs Brian & Kechris Katerina, 2013. "A graphical model method for integrating multiple sources of genome-scale data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 12(4), pages 469-487, August.
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KeywordsGaussian mixture models; Factor analysis; EM-algorithm;
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