Dempster, Laird and Rubin: maximum likelihood from incomplete data via the EM algorithm

What changed

Presented a general expectation–maximization framework for iteratively computing maximum-likelihood estimates from incomplete-data problems and established monotonic likelihood behavior under its stated conditions.

Scientific scope

The record is the exact 1977 JRSS Series B paper. Earlier special-case missing-data procedures, the Baum–Welch algorithm, later convergence refinements, variational methods and software implementations remain separate.

Evidence

The linked sources identify this contribution and its scope. WRS has not independently reconstructed the scientific claims. The record is the exact 1977 JRSS Series B paper. Earlier special-case missing-data procedures, the Baum–Welch algorithm, later convergence refinements, variational methods and software implementations remain separate.

Contributors

• A. P. Dempster · SCIENCE: Named source author of the scoped work; individual effort shares are not measured.
• N. M. Laird · SCIENCE: Named source author of the scoped work; individual effort shares are not measured.
• D. B. Rubin · SCIENCE: Named source author of the scoped work; individual effort shares are not measured.

• JSTOR record for the EM algorithm paper
• Crossref record for the EM algorithm paper

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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