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Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models

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  • Biernacki, Christophe
  • Celeux, Gilles
  • Govaert, Gerard
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    File URL: http://www.sciencedirect.com/science/article/B6V8V-472JRC1-S/2/47b17de2304f81daa2b2e3e0e7194b45
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    Bibliographic Info

    Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

    Volume (Year): 41 (2003)
    Issue (Month): 3-4 (January)
    Pages: 561-575

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    Handle: RePEc:eee:csdana:v:41:y:2003:i:3-4:p:561-575

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    Web page: http://www.elsevier.com/locate/csda

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    1. Celeux, Gilles & Govaert, Gerard, 1992. "A classification EM algorithm for clustering and two stochastic versions," Computational Statistics & Data Analysis, Elsevier, vol. 14(3), pages 315-332, October.
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    Cited by:
    1. Jeremy T. Fox & Kyoo il Kim, 2011. "A Simple Nonparametric Approach to Estimating the Distribution of Random Coefficients in Structural Models," NBER Working Papers 17283, National Bureau of Economic Research, Inc.
    2. Martinez, M.J. & Lavergne, C. & Trottier, C., 2009. "A mixture model-based approach to the clustering of exponential repeated data," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 1938-1951, October.
    3. Schumacher, Christian & Breitung, Jörg, 2008. "Real-time forecasting of German GDP based on a large factor model with monthly and quarterly data," International Journal of Forecasting, Elsevier, vol. 24(3), pages 386-398.
    4. Luca Bagnato & Antonio Punzo, 2013. "Finite mixtures of unimodal beta and gamma densities and the $$k$$ -bumps algorithm," Computational Statistics, Springer, vol. 28(4), pages 1571-1597, August.
    5. Tao, Jian & Shi, Ning-Zhong & Lee, S.-Y.Sik-Yum, 2004. "Drug risk assessment with determining the number of sub-populations under finite mixture normal models," Computational Statistics & Data Analysis, Elsevier, vol. 46(4), pages 661-676, July.
    6. Xiao-Hua Zhou & Pete Castelluccio & Chuan Zhou, 2004. "Non-Parametric Estimation of ROC Curves in the Absence of a Gold Standard," UW Biostatistics Working Paper Series 1064, Berkeley Electronic Press.
    7. Bartolucci, Francesco & Giorgio E., Montanari & Pandolfi, Silvia, 2012. "Item selection by an extended Latent Class model: An application to nursing homes evaluation," MPRA Paper 38757, University Library of Munich, Germany.
    8. Pleydell, David R.J. & Chrétien, Stéphane, 2010. "Mixtures of GAMs for habitat suitability analysis with overdispersed presence/absence data," Computational Statistics & Data Analysis, Elsevier, vol. 54(5), pages 1405-1418, May.
    9. Patrick Bajari & Jeremy T. Fox & Kyoo il Kim & Stephen P. Ryan, 2009. "A Simple Nonparametric Estimator for the Distribution of Random Coefficients," NBER Working Papers 15210, National Bureau of Economic Research, Inc.
    10. Reddy, Chandan K. & Rajaratnam, Bala, 2010. "Learning mixture models via component-wise parameter smoothing," Computational Statistics & Data Analysis, Elsevier, vol. 54(3), pages 732-749, March.
    11. Galimberti, Giuliano & Soffritti, Gabriele, 2014. "A multivariate linear regression analysis using finite mixtures of t distributions," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 138-150.
    12. Melnykov, Volodymyr & Melnykov, Igor, 2012. "Initializing the EM algorithm in Gaussian mixture models with an unknown number of components," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1381-1395.
    13. Bettina Grün & Friedrich Leisch, . "FlexMix Version 2: Finite Mixtures with Concomitant Variables and Varying and Constant Parameters," Journal of Statistical Software, American Statistical Association, vol. 28(i04).
    14. Elena Di Bernardino & Didier Rullière, 2012. "Distortions of multivariate risk measures: a level-sets based approach," Working Papers hal-00756387, HAL.
    15. Di Bernardino, Elena & Rullière, Didier, 2013. "Distortions of multivariate distribution functions and associated level curves: Applications in multivariate risk theory," Insurance: Mathematics and Economics, Elsevier, vol. 53(1), pages 190-205.
    16. Bohning, Dankmar & Seidel, Wilfried, 2003. "Editorial: recent developments in mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 349-357, January.
    17. 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.
    18. Maria Iannario, 2012. "Preliminary estimators for a mixture model of ordinal data," Advances in Data Analysis and Classification, Springer, vol. 6(3), pages 163-184, October.
    19. Basso, Rodrigo M. & Lachos, Víctor H. & Cabral, Celso Rômulo Barbosa & Ghosh, Pulak, 2010. "Robust mixture modeling based on scale mixtures of skew-normal distributions," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 2926-2941, December.
    20. Saâdaoui, Foued, 2010. "Acceleration of the EM algorithm via extrapolation methods: Review, comparison and new methods," Computational Statistics & Data Analysis, Elsevier, vol. 54(3), pages 750-766, March.
    21. Kerekes, Monika, 2012. "Growth miracles and failures in a Markov switching classification model of growth," Journal of Development Economics, Elsevier, vol. 98(2), pages 167-177.
    22. repec:hal:wpaper:hal-00750873 is not listed on IDEAS
    23. Biernacki, Christophe & Celeux, Gilles & Govaert, Gerard & Langrognet, Florent, 2006. "Model-based cluster and discriminant analysis with the MIXMOD software," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 587-600, November.

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