Latent Spatial Variable Models
Latent Spatial Variable Models is a statistical modeling framework that belongs to the class of spatial process models, distinguished by its incorporation of unobserved (latent) spatially structured variables to account for underlying spatial dependencies and heterogeneity in observed data.
46
Publications
2.6K
Citations
120
Authors
73
Institutions
Publications per year
2017–2026
10
Parents
46
Principal Component Analysis on Spatial Data: An Overview
Urška Demšar, Paul Harris, Chris Brunsdon et al. · Annals of the Association of American Geographers · 2012 · 505 citations
Computing, Geography, Geoinformatics +16
Alexandros Gryparis, Brent A. Coull, Joel Schwartz et al. · Journal of the Royal Statistical Society Series C (Applied Statistics) · 2007 · 123 citations · Full text
1–5 of 46
120
Medical University of South Carolina, United States
3 publications · 77 citations
3
h-index
2
h-index
2
h-index
2
h-index
2
h-index
1–5 of 120
73
Medical University of South Carolina
Charleston, United States
4 h-index
7 publications
188 citations

University of Minnesota
Minneapolis, United States
3 h-index
6 publications
363 citations
Norwegian University of Science and Technology
Trondheim, Norway
3 h-index
6 publications
659 citations
North Carolina State University
Raleigh, United States
3 h-index
4 publications
129 citations

Imperial College London
London, United Kingdom
2 h-index
2 publications
81 citations
University of Missouri
Columbia, United States
2 h-index
4 publications
132 citations

Universidad Tecnológica de Bolívar
Cartagena, Colombia
1 h-index
1 publications
54 citations

Harvard University Press
Cambridge, United States
1 h-index
4 publications
492 citations
1–8 of 73
3 publications · 202 citations
3
h-index
2 publications · 141 citations
2
h-index
2 publications · 88 citations
2
h-index
2 publications · 33 citations
2
h-index
2 publications · 421 citations
2
h-index
1–5