Expectation-maximization Imputation
Expectation-Maximization Imputation is a statistical imputation method that iteratively applies the expectation-maximization algorithm to estimate missing data by maximizing the likelihood of observed data under an assumed probability model.
188
Publications
15.7K
Citations
559
Authors
321
Institutions
Publications per year
2017–2026
78
Parents
188
1–5 of 188
559
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321
Texas A&M University
College Station, United States
5 h-index
14 publications
445 citations

Pennsylvania State University
State College, United States
4 h-index
7 publications
625 citations
University of Michigan
Ann Arbor, United States
4 h-index
5 publications
101 citations
University of Oxford
Oxford, United Kingdom
3 h-index
9 publications
427 citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
8 publications
494 citations

The University of Queensland
Brisbane, Australia
2 h-index
3 publications
69 citations
National Institute of Allergy and Infectious Diseases
Bethesda, United States
2 h-index
7 publications
146 citations

U.S. National Science Foundation
Alexandria, United States
2 h-index
3 publications
89 citations
1–8 of 321
6 publications · 2.6K citations
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4 publications · 318 citations
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CSDA · 5 publications · 136 citations
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4 publications · 373 citations
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AJE · 3 publications · 340 citations
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1–5