Spatial Regression

Spatial Regression is a statistical modeling technique that extends traditional regression analysis by incorporating spatial dependencies and heterogeneities among observations to account for the non-independence of georeferenced data.

1.8K

Publications

166.1K

Citations

4.4K

Authors

1.7K

Institutions

Publications per year

2017–2026

725

Authors

4.4K

  1. DA
    Daniel A. Griffith

    The University of Texas at Dallas, United States

    32 publications · 5.4K citations

    24

    h-index

  2. LA
    Luc Anselin

    Arizona State University, United States

    27 publications · 10.7K citations

    24

    h-index

  3. AS
    A. Stewart Fotheringham

    Arizona State University, United States

    23 publications · 10.2K citations

    22

    h-index

  4. CB
    Chris Brunsdon

    National University of Ireland, Maynooth, Ireland

    23 publications · 7.8K citations

    21

    h-index

  5. MC
    Martin Charlton

    National University of Ireland, Maynooth, Ireland

    23 publications · 7.7K citations

    21

    h-index

1–5 of 4.4K

Venues

  1. Geographical Analysis

    55 publications · 12K citations

    31

    h-index

  2. Environment and Planning A Economy and Space

    33 publications · 5K citations

    29

    h-index

  3. Journal of the American Statistical Association

    32 publications · 4.9K citations

    26

    h-index

  4. 23

    h-index

  5. Sustainability

    44 publications · 1.1K citations

    22

    h-index

1–5