Spatial Dependence Testing

Spatial Dependence Testing is a statistical methodology used in spatial analysis to determine whether the values of a variable at different locations are interdependent, distinguished by its focus on assessing the presence and structure of spatial autocorrelation in georeferenced data.

296

Publications

27.2K

Citations

598

Authors

385

Institutions

Publications per year

2017–2026

66

Variants

Spatial Autocorrelation Testing

Authors

598

  1. LA
    Luc Anselin

    Arizona State University, United States

    10 publications · 3.7K citations

    10

    h-index

  2. BH
    Badi H. Baltagi

    Syracuse University, United States

    9 publications · 767 citations

    9

    h-index

  3. JM
    Jesús Mur

    Universidad de Zaragoza, Spain

    7 publications · 267 citations

    7

    h-index

  4. MR
    Manuel Ruiz Marín

    Universidad Politécnica de Cartagena, Spain

    5 publications · 175 citations

    5

    h-index

  5. LL
    Lung‐fei Lee

    The Ohio State University, United States

    5 publications · 166 citations

    5

    h-index

1–5 of 598

Venues

  1. Regional Science and Urban Economics

    17 publications · 3.6K citations

    16

    h-index

  2. Papers of the Regional Science Association

    12 publications · 776 citations

    12

    h-index

  3. Environment and Planning A Economy and Space

    10 publications · 973 citations

    10

    h-index

  4. SSRN Electronic Journal

    Repository · 10 publications · 379 citations

    10

    h-index

  5. Geographical Analysis

    11 publications · 7.9K citations

    10

    h-index

1–5