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EM algorithms without missing data
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
doi:10.1177/096228029700600104
pmid:9185289
fatcat:44slrt4g3batlf547j5wsvd57e