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EM Algorithms

  • Charles Byrne
  • Paul P. B. Eggermont

Maximum Likelihood Estimation

Expectation-Maximization algorithms, or em algorithms for short, are iterative algorithms designed to solve maximum likelihood estimation problems. The general setting is that one observes a random sample \({Y }_{1},{Y }_{2},\ldots,{Y }_{n}\)

Keywords

Conditional Expectation Probability Vector Monotonicity Property Leibler Divergence Algebraic Reconstruction Technique 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Charles Byrne
  • Paul P. B. Eggermont

There are no affiliations available

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