Likelihood Surface Analysis
Likelihood Surface Analysis is a computational method in statistical inference that characterizes the structure of the likelihood function across parameter space to identify maxima, assess parameter identifiability, and evaluate model sensitivity by examining the shape and topology of the likelihood surface.
29
Publications
2.4K
Citations
93
Authors
73
Institutions
Publications per year
2017–2026
4
Parents
29
On Convergence Properties of the EM Algorithm for Gaussian Mixtures
Lei Xu, Michael I. Jordan · Neural Computation · 1996 · 763 citations
The Coalescent Process With Selfing
Magnus Nordborg, Peter Donnelly · Genetics · 1997 · 196 citations · Full text
Use of the MULTINEST algorithm for gravitational wave data analysis
Farhan Feroz, J. R. Gair, Michael P. Hobson et al. · Classical and Quantum Gravity · 2009 · 96 citations · Full text
Natural Sciences, Astronomy, Physics +14
1–5 of 29
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Gregor Mendel Institute of Molecular Plant Biology, Austria
2 publications · 232 citations
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1–5 of 93
73
King's College London
London, United Kingdom
2 h-index
2 publications
206 citations
University College London
London, United Kingdom
2 h-index
3 publications
148 citations

University of Warsaw
Warsaw, Poland
2 h-index
2 publications
206 citations
Consejo Superior de Investigaciones Científicas
Madrid, Spain
2 h-index
2 publications
206 citations

National and Kapodistrian University of Athens
Athens, Greece
2 h-index
2 publications
206 citations
University of Illinois Urbana-Champaign
Urbana, United States
2 h-index
2 publications
114 citations
Institute of Nuclear and Particle Physics
Athens, Greece
2 h-index
2 publications
206 citations

University of Bristol
Bristol, United Kingdom
2 h-index
2 publications
206 citations
1–8 of 73
3 publications · 88 citations
3
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2 publications · 90 citations
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MBE · 2 publications · 186 citations
2
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Repository · 2 publications · 99 citations
2
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2 publications · 93 citations
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