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Methods for merging Gaussian mixture components


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  • Christian Hennig


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    Article provided by Springer in its journal Advances in Data Analysis and Classification.

    Volume (Year): 4 (2010)
    Issue (Month): 1 (April)
    Pages: 3-34

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    Handle: RePEc:spr:advdac:v:4:y:2010:i:1:p:3-34

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    Keywords: Model-based cluster analysis; Multilayer mixture; Unimodality; Prediction strength; Ridgeline; Dip test; 62H30;

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    1. Weiliang Qiu & Harry Joe, 2006. "Generation of Random Clusters with Specified Degree of Separation," Journal of Classification, Springer, vol. 23(2), pages 315-334, September.
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    Cited by:
    1. Christian Hennig, 2013. "Discussion of “Model-based clustering with non-normal mixture distributions” by S. X. Lee and G. J. McLachlan," Statistical Methods and Applications, Springer, vol. 22(4), pages 455-458, November.
    2. Adolfo Álvarez & Daniel Peña, 2013. "Recombining partitions via unimodality tests," Statistics and Econometrics Working Papers ws130706, Universidad Carlos III, Departamento de Estadística y Econometría.
    3. Coffey, N. & Hinde, J. & Holian, E., 2014. "Clustering longitudinal profiles using P-splines and mixed effects models applied to time-course gene expression data," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 14-29.
    4. Melnykov, Volodymyr, 2013. "On the distribution of posterior probabilities in finite mixture models with application in clustering," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 175-189.
    5. Kim, Daeyoung & Seo, Byungtae, 2014. "Assessment of the number of components in Gaussian mixture models in the presence of multiple local maximizers," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 100-120.
    6. Adolfo Álvarez & Daniel Peña, 2014. "Recombining partitions from multivariate data: a clustering method on Bayes factors," Statistics and Econometrics Working Papers ws1450804, Universidad Carlos III, Departamento de Estadística y Econometría.


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