Likelihood Approximation
Likelihood Approximation is a computational method that belongs to the class of statistical techniques used to estimate likelihood functions, distinguished by its reliance on simplifying assumptions or numerical procedures to approximate intractable or complex likelihoods when exact evaluation is impractical.
180
Publications
15.4K
Citations
343
Authors
217
Institutions
Publications per year
2017–2026
36
Parents
180
Mixture Densities, Maximum Likelihood and the EM Algorithm
Richard A. Redner, Homer F. Walker · SIAM Review · 1984 · 2.7K citations
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217

Centre National de la Recherche Scientifique
Paris, France
7 h-index
12 publications
516 citations

Aarhus University
Aarhus, Denmark
5 h-index
5 publications
557 citations

University of Edinburgh
Edinburgh, United Kingdom
4 h-index
6 publications
651 citations
Max Planck Institute for Intelligent Systems
Stuttgart, Germany
4 h-index
6 publications
133 citations
Stanford University
Stanford, United States
4 h-index
4 publications
334 citations

University of Minnesota
Minneapolis, United States
4 h-index
6 publications
1.2K citations
National University of Singapore
Singapore, Singapore
3 h-index
5 publications
99 citations
California Institute of Technology
Pasadena, United States
3 h-index
4 publications
113 citations
1–8 of 217
12 publications · 977 citations
12
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14 publications · 1.1K citations
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Repository · 8 publications · 264 citations
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JCGS · 6 publications · 1.6K citations
6
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ApJ · 5 publications · 182 citations
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