Hierarchical Spatial Model is a statistical modeling framework that belongs to the class of hierarchical models by incorporating multiple levels of variation, distinguished by its explicit integration of spatial dependence structures at one or more levels to account for geographic or spatially indexed heterogeneity in the data-generating process.
226
Publications
14.7K
Citations
632
Authors
387
Institutions
Publications per year
2017–2026
52
Publications
226
1–5 of 226
Authors
632
- SB
11
h-index
- AE
10
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- BP
8
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- AO
6
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- GD
4
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1–5 of 632
Institutions
387
University of Minnesota
Minneapolis, United States
15 h-index
26 publications
3.7K citations
Duke University
Durham, United States
9 h-index
13 publications
2.5K citations
United States Geological Survey
Reston, United States
8 h-index
20 publications
3K citations
Pennsylvania State University
State College, United States
7 h-index
7 publications
303 citations
Michigan State University
East Lansing, United States
6 h-index
9 publications
1.5K citations
NOAA National Marine Fisheries Service Alaska Fisheries Science Center
Seattle, United States
5 h-index
10 publications
617 citations
Imperial College London
London, United Kingdom
5 h-index
21 publications
697 citations
University of Connecticut
Storrs, United States
5 h-index
5 publications
1.2K citations
1–8 of 387
Venues
- Environment and Planning A Economy and Space
6 publications · 461 citations
6
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- Biometrics
6 publications · 301 citations
6
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- Ecological Modelling
6 publications · 741 citations
6
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- Geographical Analysis
5 publications · 374 citations
5
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- Journal of the American Statistical Association
4 publications · 679 citations
4
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1–5