Spatial Random Effects Models

Spatial Random Effects Models is a statistical modeling framework that belongs to the class of mixed-effects models, distinguished by its incorporation of spatially correlated random effects to account for unobserved geographical dependencies in data.

393

Publications

30.1K

Citations

936

Authors

502

Institutions

Publications per year

2017–2026

116

Variants

Spatial Random Effects Model

Authors

936

  1. NC
    Noel Cressie

    Iowa State University, United States

    16 publications · 2.7K citations

    15

    h-index

  2. AE
    Alan E. Gelfand

    Duke University, United States

    10 publications · 1.7K citations

    10

    h-index

  3. DA
    Daniel A. Griffith

    The University of Texas at Dallas, United States

    9 publications · 662 citations

    9

    h-index

  4. SB
    Sudipto Banerjee

    University of Minnesota, United States

    8 publications · 1.1K citations

    8

    h-index

  5. BH
    Badi H. Baltagi

    Syracuse University, United States

    7 publications · 396 citations

    7

    h-index

1–5 of 936

Venues

  1. Biometrics

    13 publications · 3.2K citations

    13

    h-index

  2. Journal of the American Statistical Association

    12 publications · 2.6K citations

    12

    h-index

  3. Statistics in Medicine

    9 publications · 257 citations

    9

    h-index

  4. SSRN Electronic Journal

    Repository · 9 publications · 228 citations

    9

    h-index

  5. Geographical Analysis

    8 publications · 307 citations

    8

    h-index

1–5