Likelihood For Missing Data
Likelihood for Missing Data is a statistical framework that specifies the probability of observed data under a given model while accounting for the uncertainty introduced by unobserved or missing values through formal probabilistic integration over the missing data mechanism.
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69.3K
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320
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235
Institutions
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2017–2026
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Predicting missing links via local information
Tao Zhou, Linyuan Lü, Yi‐Cheng Zhang · The European Physical Journal B · 2009 · 1.8K citations · Full text
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University of North Carolina at Chapel Hill, United States
4 publications · 111 citations
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University of Chicago
Chicago, United States
8 h-index
10 publications
781 citations

Beijing University of Technology
Beijing, China
6 h-index
12 publications
295 citations
Harvard University
Cambridge, United States
6 h-index
10 publications
151.4K citations
University at Buffalo, State University of New York
Buffalo, United States
5 h-index
7 publications
177 citations

Guangxi Normal University
Guilin, China
4 h-index
7 publications
108 citations

Centre National de la Recherche Scientifique
Paris, France
4 h-index
6 publications
189 citations
University of Michigan
Ann Arbor, United States
4 h-index
4 publications
116 citations

University of Waterloo
Waterloo, Canada
4 h-index
8 publications
150 citations
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18 publications · 2K citations
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CSDA · 9 publications · 215 citations
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9 publications · 52.5K citations
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