Spatial Mixed Models is a type of mixed-effects model that incorporates spatially correlated random effects to account for geographical or spatial dependence in hierarchical or clustered data.
135
Publications
11.3K
Citations
316
Authors
206
Institutions
Publications per year
2017–2026
32
Variants
Spatial Mixed-effects Models
Parents
Publications
135
1–5 of 135
Authors
316
- DM
4
h-index
- LA
4
h-index
- DA
3
h-index
- PW
3
h-index
- CW
3
h-index
1–5 of 316
Institutions
206
University of Minnesota
Minneapolis, United States
6 h-index
7 publications
757 citations
University of Florida
Gainesville, United States
4 h-index
8 publications
319 citations
North Carolina State University
Raleigh, United States
4 h-index
7 publications
382 citations
Duke University
Durham, United States
3 h-index
4 publications
132 citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
3 h-index
4 publications
139 citations
University of Bristol
Bristol, United Kingdom
3 h-index
4 publications
350 citations
National Cheng Kung University
Tainan City, Taiwan
3 h-index
10 publications
295 citations
National Health Research Institutes
Hsinchu, Taiwan
3 h-index
5 publications
142 citations
1–8 of 206
Venues
- Geographical Analysis
8 publications · 515 citations
8
h-index
- Biometrics
6 publications · 1.2K citations
6
h-index
- Computational Statistics & Data Analysis
CSDA · 5 publications · 172 citations
5
h-index
- Journal of the American Statistical Association
5 publications · 1.7K citations
5
h-index
- Ecography
3 publications · 436 citations
3
h-index
1–5