Stochastic versions of the em algorithm: an experimental study in the mixture case
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Publication:4346970
DOI10.1080/00949659608811772zbMath0907.62024OpenAlexW2050341350MaRDI QIDQ4346970
Gilles Celeux, Didier Chauveau, Jean Diebolt
Publication date: 8 March 1999
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949659608811772
Point estimation (62F10) Monte Carlo methods (65C05) Probabilistic methods, stochastic differential equations (65C99)
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Cites Work
- On the convergence properties of the EM algorithm
- Almost sure convergence of a class of stochastic algorithms
- Convergence of a stochastic approximation version of the EM algorithm
- Some recent research in the analysis of mixture distributions
- Mixture Densities, Maximum Likelihood and the EM Algorithm
- Classification and Mixture Approaches to Clustering via Maximum Likelihood
- The Calculation of Posterior Distributions by Data Augmentation
- Estimation of parameters in hidden Markov models
- Asymptotic properties of a stochastic EM Algorithm for estimating mixing proportions
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