Bayesian Spatial Smoothing
Bayesian Spatial Smoothing is a statistical modeling framework that incorporates prior distributions over spatially correlated parameters to estimate smoothed spatial patterns, distinguishing itself from classical spatial smoothing methods by formally accounting for uncertainty through Bayesian inference.
47
Publications
2.1K
Citations
118
Authors
75
Institutions
Publications per year
2017–2026
10
Parents
47
Smoothing Regional Maps Using Empirical Bayes Predictors
Noel Cressie · Geographical Analysis · 1992 · 106 citations · Full text
Computing, Biostatistics, Geography +15
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University of California, Berkeley, United States
2 publications · 556 citations
2
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1–5 of 118
75
University of Michigan
Ann Arbor, United States
4 h-index
8 publications
422 citations

University of Minnesota
Minneapolis, United States
4 h-index
14 publications
742 citations
ARC Centre of Excellence for Mathematical and Statistical Frontiers
Parkville, Australia
3 h-index
7 publications
270 citations

Queensland University of Technology
Brisbane, Australia
3 h-index
8 publications
356 citations

University of Warwick
Coventry, United Kingdom
2 h-index
4 publications
94 citations

Harvard University Press
Cambridge, United States
2 h-index
2 publications
511 citations
Harvard University
Cambridge, United States
2 h-index
2 publications
556 citations
University of Connecticut
Storrs, United States
2 h-index
3 publications
176 citations
1–8 of 75
4 publications · 94 citations
4
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3 publications · 518 citations
3
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2 publications · 169 citations
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JCGS · 2 publications · 77 citations
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2 publications · 114 citations
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