Optimal Bandwidth Selection

Optimal Bandwidth Selection is a methodological procedure in spatial statistics that determines the most appropriate scale of analysis for kernel density estimation by balancing spatial resolution and statistical reliability to accurately identify significant hot spots.

293

Publications

21.7K

Citations

548

Authors

324

Institutions

Publications per year

2017–2026

55

Authors

548

  1. JS
    J. S. Marron

    University of North Carolina at Chapel Hill, United States

    11 publications · 1.6K citations

    11

    h-index

  2. TG
    Théo Gasser

    University of Zurich, Switzerland

    5 publications · 648 citations

    5

    h-index

  3. RJ
    Rob J. Hyndman

    Monash University, Australia

    5 publications · 522 citations

    5

    h-index

  4. MD
    Matias D. Cattaneo

    University of Michigan, United States

    5 publications · 1.3K citations

    5

    h-index

  5. SC
    Sebastián Calónico

    Columbia University, United States

    5 publications · 1.5K citations

    5

    h-index

1–5 of 548

Venues

  1. The Annals of Statistics

    30 publications · 4.8K citations

    27

    h-index

  2. Journal of the American Statistical Association

    13 publications · 1.7K citations

    13

    h-index

  3. Computational Statistics & Data Analysis

    CSDA · 12 publications · 944 citations

    11

    h-index

  4. Journal of nonparametric statistics

    14 publications · 390 citations

    11

    h-index

  5. Statistics & Probability Letters

    9 publications · 233 citations

    9

    h-index

1–5