Maximum likelihood estimation via the ECM algorithm: A general framework

  title={Maximum likelihood estimation via the ECM algorithm: A general framework},
  author={Xiao-Li Meng and Donald B. Rubin},
Two major reasons for the popularity of the EM algorithm are that its maximum step involves only complete-data maximum likelihood estimation, which is often computationally simple, and that its convergence is stable, with each iteration increasing the likelihood. When the associated complete-data maximum likelihood estimation itself is complicated, EM is less attractive because the M-step is computationally unattractive. In many cases, however, complete-data maximum likelihood estimation is… 
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