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Dimensionally Reduced Model-Based Clustering Through Mixtures of Factor Mixture Analyzers

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  • Cinzia Viroli

Abstract

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  • Cinzia Viroli, 2010. "Dimensionally Reduced Model-Based Clustering Through Mixtures of Factor Mixture Analyzers," Journal of Classification, Springer;The Classification Society, vol. 27(3), pages 363-388, November.
  • Handle: RePEc:spr:jclass:v:27:y:2010:i:3:p:363-388
    DOI: 10.1007/s00357-010-9063-7
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    References listed on IDEAS

    as
    1. Chris Fraley & Adrian E. Raftery, 2003. "Enhanced Model-Based Clustering, Density Estimation, and Discriminant Analysis Software: MCLUST," Journal of Classification, Springer;The Classification Society, vol. 20(2), pages 263-286, September.
    2. 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.
    3. Chris Fraley & Adrian E. Raftery, 1999. "MCLUST: Software for Model-Based Cluster Analysis," Journal of Classification, Springer;The Classification Society, vol. 16(2), pages 297-306, July.
    4. S. Ganesalingam & G. J. McLachlan, 1979. "A Case Study of two Clustering Methods based on Maximum Likelihood," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 33(2), pages 81-90, June.
    5. Olvi L. Mangasarian & W. Nick Street & William H. Wolberg, 1995. "Breast Cancer Diagnosis and Prognosis Via Linear Programming," Operations Research, INFORMS, vol. 43(4), pages 570-577, August.
    6. 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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    Citations

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    Cited by:

    1. 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.
    2. Paul D. McNicholas, 2016. "Model-Based Clustering," Journal of Classification, Springer;The Classification Society, vol. 33(3), pages 331-373, October.
    3. 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.
    4. 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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