Bayesian Smoothing
Bayesian Smoothing is a statistical inference method that belongs to the class of Bayesian estimation techniques, distinguished by its use of posterior distributions to estimate latent states in a time series by incorporating all available observational data, both past and future, to refine probabilistic beliefs about unobserved states.
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9.3K
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286
Authors
163
Institutions
Publications per year
2017–2026
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Likelihood analysis of non-Gaussian measurement time series
Neil Shephard · Biometrika · 1997 · 693 citations
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Texas A&M University
College Station, United States
3 h-index
5 publications
122 citations

The University of Melbourne
Melbourne, Australia
3 h-index
3 publications
107 citations
Los Alamos National Laboratory
Los Alamos, United States
3 h-index
5 publications
198 citations
University of Cambridge
Cambridge, United Kingdom
3 h-index
3 publications
1.1K citations
University of Wisconsin–Madison
Madison, United States
3 h-index
4 publications
57 citations
University of Missouri
Columbia, United States
3 h-index
4 publications
185 citations
North Carolina State University
Raleigh, United States
2 h-index
4 publications
194 citations
Laboratoire Traitement et Communication de l’Information
Palaiseau, France
2 h-index
4 publications
2.1K citations
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13 publications · 934 citations
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7 publications · 951 citations
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Repository · 4 publications · 225 citations
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Repository · 4 publications · 432 citations
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4 publications · 151 citations
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