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

Author:

Biernacki Christophe,Celeux Gilles,Govaert Gérard

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Theory and Mathematics,Computational Mathematics,Statistics and Probability

Reference18 articles.

1. A new look at the statistical identification model;Akaike;IEEE Trans. Automat. Control,1974

2. Computer-Assisted Analysis of Mixtures and Applications: Meta-Analysis, Disease Mapping and Others;Böhning,1999

3. A classification EM algorithm and two stochastic versions;Celeux;Comput. Stat. Data Anal.,1992

4. A component-wise EM algorithm for mixtures;Celeux;J. Comput. Graph. Stat.,2001

5. Detecting features in spatial point process with clutter viamodel-based clustering;Dasgupta;J. Am. Stat. Assoc.,1998

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