EM algorithms without missing data

Mark P Becker, Ilsoon Yang, Kenneth Lange
1997 Statistical Methods in Medical Research  
Most problems in computational statistics involve optimization of an objective function such as a loglikelihood, a sum of squares, or a log posterior function. The EM algorithm is one of the most effective algorithms for maximization because it iteratively transfers maximization from a complex function to a simple, surrogate function. This theoretical perspective clari®es the operation of the EM algorithm and suggests novel generalizations. Besides simplifying maximization, optimization
more » ... usually leads to highly stable algorithms with well-understood local and global convergence properties. Although convergence can be excruciatingly slow, various devices exist for accelerating it. Beginning with the EM algorithm, we review in this paper several optimization transfer algorithms of substantial utility in medical statistics.
doi:10.1177/096228029700600104 pmid:9185289 fatcat:44slrt4g3batlf547j5wsvd57e