Bootstrap For Spatial Data

Bootstrap for Spatial Data is a resampling technique that extends the bootstrap method to spatial datasets by preserving spatial dependence structures through specialized sampling schemes that account for spatial autocorrelation and geographic proximity.

29

Publications

972

Citations

73

Authors

53

Institutions

Publications per year

2017–2026

9

Authors

73

  1. SN
    Soumendra N. Lahiri

    Iowa State University, United States

    2 publications · 98 citations

    2

    h-index

  2. JM
    Jorge Mateu

    Universitat Jaume I, Spain

    2 publications · 171 citations

    2

    h-index

  3. PJ
    Peter J. Diggle

    Lancaster University, United Kingdom

    2 publications · 171 citations

    2

    h-index

  4. JZ
    Jun Zhu

    University of Wisconsin–Madison, United States

    2 publications · 86 citations

    2

    h-index

  5. HE
    Helen E. Clough

    University of Liverpool, United Kingdom

    2 publications · 171 citations

    2

    h-index

1–5 of 73

Venues

  1. Computational Statistics & Data Analysis

    CSDA · 3 publications · 36 citations

    3

    h-index

  2. Journal of Econometrics

    2 publications · 69 citations

    2

    h-index

  3. Advances in Applied Probability

    AAP · 2 publications · 171 citations

    2

    h-index

  4. Statistical Science

    1 publications · 32 citations

    1

    h-index

  5. Stat

    1 publications · 37 citations

    1

    h-index

1–5