Model-based Spatial Clustering

Model-Based Spatial Clustering is a spatial clustering approach that belongs to the class of model-based clustering methods, distinguished by its incorporation of spatial dependencies and geographical structure into probabilistic or statistical models to identify regions of similar attributes or point patterns.

54

Publications

4K

Citations

185

Authors

108

Institutions

Publications per year

2017–2026

17

Authors

185

  1. AE
    Adrian E. Raftery

    University of Washington, United States

    7 publications · 1.2K citations

    7

    h-index

  2. CF
    Chris Fraley

    University of Washington, United States

    5 publications · 582 citations

    5

    h-index

  3. WK
    Way Kuo

    University of Tennessee at Knoxville, United States

    2 publications · 98 citations

    2

    h-index

  4. BH
    Bernhard Hausdorf

    Universität Hamburg, Germany

    2 publications · 167 citations

    2

    h-index

  5. YD
    Yu Deng

    Institute of Geographic Sciences and Natural Resources Research, China

    2 publications · 45 citations

    2

    h-index

1–5 of 185

Venues

  1. 3

    h-index

  2. Technometrics

    2 publications · 78 citations

    2

    h-index

  3. Energy Economics

    2 publications · 49 citations

    2

    h-index

  4. Machine Learning

    2 publications · 311 citations

    2

    h-index

  5. Applied Ocean Research

    1 publications · 23 citations

    1

    h-index

1–5