Bayesian Spatial Prediction
Bayesian Spatial Prediction is a statistical framework for spatial inference that formally quantifies uncertainty in predicted values at unobserved locations by combining prior distributions over spatial processes with observed data through Bayes' theorem.
139
Publications
7.5K
Citations
428
Authors
261
Institutions
Publications per year
2017–2026
36
Parents
139
Building Statistical Models To Analyze Species Distributions
Andrew M. Latimer, Shanshan Wu, Alan E. Gelfand et al. · Ecological Applications · 2006 · 368 citations
Bayesian Geostatistical Design
Peter J. Diggle, Søren Lophaven · Scandinavian Journal of Statistics · 2005 · 230 citations · Full text
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261

University of British Columbia
Vancouver, Canada
7 h-index
18 publications
681 citations

The University of Queensland
Brisbane, Australia
6 h-index
10 publications
470 citations
UCLouvain
Louvain-la-Neuve, Belgium
5 h-index
13 publications
496 citations
Michigan State University
East Lansing, United States
5 h-index
11 publications
431 citations
Swiss Tropical and Public Health Institute
Allschwil, Switzerland
4 h-index
15 publications
1.3K citations
London School of Hygiene & Tropical Medicine
London, United Kingdom
4 h-index
10 publications
992 citations

Imperial College London
London, United Kingdom
4 h-index
9 publications
1.1K citations
Duke University
Durham, United States
3 h-index
3 publications
437 citations
1–8 of 261
6 publications · 280 citations
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6 publications · 310 citations
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JCGS · 4 publications · 123 citations
4
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4 publications · 471 citations
4
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3 publications · 646 citations
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