Maximum Likelihood from Incomplete Data via the EM Algorithm

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Maximum Likelihood from Incomplete Data via the EM Algorithm

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Title: Maximum Likelihood from Incomplete Data via the EM Algorithm
Author: Dempster, Arthur P.; Laird, Nan M.; Rubin, Donald B.

Note: Order does not necessarily reflect citation order of authors.

Citation: Dempster, Arthur P, Nan M. Laird, and Donald B. Rubin. 1976. Maximum Likelihood from Incomplete Data via the EM Algorithm. Paper presented at the Royal Statistical Society at a meeting organized by the Research Section, December 8, 1976.
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Abstract: A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behavior of the likelihood and convergence of the algorithm is derived. Many examples are sketched, including missing value situations, applications to grouped, censored or truncated data, finite mixture models, variance component estimation, hyperparameter estimation, iteratively reweighted least squares and factor analysis.
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:3426318

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  • FAS Scholarly Articles [7501]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University
 
 

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