Choosing initial values for the EM algorithm for finite mixtures
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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
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Furman, W. David & Lindsay, Bruce G., 1994. "Testing for the number of components in a mixture of normal distributions using moment estimators," Computational Statistics & Data Analysis, Elsevier, vol. 17(5), pages 473-492, June.
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- Furman, W. David & Lindsay, Bruce G., 1994. "Measuring the relative effectiveness of moment estimators as starting values in maximizing likelihoods," Computational Statistics & Data Analysis, Elsevier, vol. 17(5), pages 493-507, June.
- Wilfried Seidel & Karl Mosler & Manfred Alker, 2000. "A Cautionary Note on Likelihood Ratio Tests in Mixture Models," Annals of the Institute of Statistical Mathematics, Springer, vol. 52(3), pages 481-487, September.
- 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.
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- Garel, Bernard, 2007. "Recent asymptotic results in testing for mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5295-5304, July.
- 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).
- Neal, Mark, 2007. "Estimating complex production functions: The importance of starting values," Risk and Sustainable Management Group Working Papers 151178, University of Queensland, School of Economics.
- Sharon Lee & Geoffrey McLachlan, 2013. "Model-based clustering and classification with non-normal mixture distributions," Statistical Methods and Applications, Springer, vol. 22(4), pages 427-454, November.
- 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.
- 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.
- Bohning, Dankmar & Seidel, Wilfried, 2003. "Editorial: recent developments in mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 349-357, January.
- 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.
- 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.
- Kerekes, Monika, 2009. "Growth miracles and failures in a Markov switching classification model of growth," Discussion Papers 2009/11, Free University Berlin, School of Business & Economics.
- 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.
- Pietro Coretto & Christian Hennig, 2010. "A simulation study to compare robust clustering methods based on mixtures," Advances in Data Analysis and Classification, Springer, vol. 4(2), pages 111-135, September.
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