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A mixture of mixture models for a classification problem: The unity measure error

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  • Di Zio, Marco
  • Guarnera, Ugo
  • Rocci, Roberto

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  • Di Zio, Marco & Guarnera, Ugo & Rocci, Roberto, 2007. "A mixture of mixture models for a classification problem: The unity measure error," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2573-2585, February.
    • Handle: RePEc:eee:csdana:v:51:y:2007:i:5:p:2573-2585
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    References listed on IDEAS

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    1. Biernacki, Christophe & Celeux, Gilles & Govaert, Gerard, 2003. "Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 561-575, January.
    2. Hathaway, Richard J., 1986. "Another interpretation of the EM algorithm for mixture distributions," Statistics & Probability Letters, Elsevier, vol. 4(2), pages 53-56, March.
    3. Adelchi Azzalini & Antonella Capitanio, 2003. "Distributions generated by perturbation of symmetry with emphasis on a multivariate skew t‐distribution," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(2), pages 367-389, May.
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    Cited by:

    1. Marco Di Zio & Ugo Guarnera, 2010. "A multiple imputation approach to deal with the unity measure error," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(3), pages 431-444, August.
    2. Alessio Farcomeni & Antonio Punzo, 2020. "Robust model-based clustering with mild and gross outliers," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(4), pages 989-1007, December.
    3. Redivo, Edoardo & Nguyen, Hien D. & Gupta, Mayetri, 2020. "Bayesian clustering of skewed and multimodal data using geometric skewed normal distributions," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
    4. Di Mari, Roberto & Bakk, Zsuzsa & Oser, Jennifer & Kuha, Jouni, 2023. "A two-step estimator for multilevel latent class analysis with covariates," LSE Research Online Documents on Economics 119994, London School of Economics and Political Science, LSE Library.
    5. Shuchismita Sarkar & Volodymyr Melnykov & Rong Zheng, 2020. "Gaussian mixture modeling and model-based clustering under measurement inconsistency," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(2), pages 379-413, June.
    6. Amovin-Assagba, Martial & Gannaz, Irène & Jacques, Julien, 2022. "Outlier detection in multivariate functional data through a contaminated mixture model," Computational Statistics & Data Analysis, Elsevier, vol. 174(C).
    7. Monica Pratesi & Claudio Ceccarelli & Stefano Menghinello, 2021. "Citizen-Generated Data and Official Statistics: an application to SDG indicators," Discussion Papers 2021/274, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.

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