Bayesian Covariance Modeling
Bayesian Covariance Modeling is a statistical framework within spatial covariance modeling that incorporates prior distributions over covariance parameters to enable probabilistic inference and uncertainty quantification in the estimation of spatial dependence structures.
15
Publications
643
Citations
35
Authors
25
Institutions
Publications per year
2017–2026
2
Parents
15
1–5 of 15
35
2
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1
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1–5 of 35
25
University of Washington
Seattle, United States
2 h-index
4 publications
390 citations
Yale University
New Haven, United States
1 h-index
2 publications
30 citations
University of California, Los Angeles
Los Angeles, United States
1 h-index
1 publications
11 citations

King Abdullah University of Science and Technology
Jeddah, Saudi Arabia
1 h-index
1 publications
11 citations
University of Florida
Gainesville, United States
1 h-index
1 publications
19 citations
Seattle University
Seattle, United States
1 h-index
1 publications
48 citations
Center for Naval Analyses
Arlington, United States
1 h-index
1 publications
14 citations
Inserm
Paris, France
1 h-index
1 publications
22 citations
1–8 of 25
1 publications · 48 citations
1
h-index
1 publications · 27 citations
1
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1 publications · 17 citations
1
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Repository · 1 publications · 10 citations
1
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1 publications · 114 citations
1
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1–5