Bayesian Spatial Variable Selection
Bayesian Spatial Variable Selection is a statistical modeling framework that identifies relevant predictors in spatially referenced data by incorporating Bayesian inference to simultaneously account for spatial dependence and uncertainty in variable inclusion through posterior probabilities.
41
Publications
1.9K
Citations
141
Authors
90
Institutions
Publications per year
2017–2026
9
Parents
41
141
Swiss Tropical and Public Health Institute, Switzerland
9 publications · 530 citations
9
h-index
5
h-index
3
h-index
3
h-index
3
h-index
1–5 of 141
90
Swiss Tropical and Public Health Institute
Allschwil, Switzerland
10 h-index
35 publications
1.9K citations

University of Basel
Basel, Switzerland
9 h-index
33 publications
1.8K citations
Ludwig-Maximilians-Universität München
Munich, Germany
3 h-index
5 publications
366 citations
Centre de Recherche en Santé de Nouna
Nouna, Burkina Faso
3 h-index
4 publications
156 citations

University of Minnesota
Minneapolis, United States
3 h-index
5 publications
141 citations
Medical University of South Carolina
Charleston, United States
3 h-index
8 publications
147 citations

Johns Hopkins University
Baltimore, United States
2 h-index
4 publications
274 citations
North Carolina State University
Raleigh, United States
2 h-index
4 publications
202 citations
1–8 of 90
JCGS · 3 publications · 206 citations
3
h-index
3 publications · 108 citations
3
h-index
2 publications · 50 citations
2
h-index
1 publications · 143 citations
2
h-index
2 publications · 107 citations
2
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1–5