Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models
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Bibliographic InfoArticle provided by Elsevier in its journal Computational Statistics & Data Analysis.
Volume (Year): 41 (2003)
Issue (Month): 3-4 (January)
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Web page: http://www.elsevier.com/locate/csda
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- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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).
- Elena Di Bernardino & Didier Rullière, 2012. "Distortions of multivariate risk measures: a level-sets based approach," Working Papers hal-00756387, HAL.
- 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.
- Elena Di Bernardino & Didier Rullière, 2013. "Distortions of multivariate distribution functions and associated level curves: applications in multivariate risk theory," Post-Print hal-00750873, HAL.
- Bohning, Dankmar & Seidel, Wilfried, 2003. "Editorial: recent developments in mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 349-357, January.
- 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.
- 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.
- 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.
- 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.
- 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.
- repec:hal:wpaper:hal-00750873 is not listed on IDEAS
- 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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