Resampling Techniques

Resampling Techniques is a statistical methodology that involves repeatedly drawing samples from a given dataset to estimate the sampling distribution of a statistic, thereby enabling inference through empirical approximation rather than analytical derivation.

2.9K

Publications

299.6K

Citations

5.8K

Authors

1.9K

Institutions

Publications per year

2017–2026

821

Authors

5.8K

  1. PH
    Peter Hall

    Australian National University, Australia

    33 publications · 2.8K citations

    25

    h-index

  2. DN
    Dimitris N. Politis

    University of California San Diego, United States

    26 publications · 5.5K citations

    22

    h-index

  3. JP
    Joseph P. Romano

    Stanford University, United States

    21 publications · 5.4K citations

    20

    h-index

  4. TM
    Taghi M. Khoshgoftaar

    Florida Atlantic University, United States

    22 publications · 4K citations

    18

    h-index

  5. JN
    J. N. K. Rao

    Carleton University, Canada

    15 publications · 1.1K citations

    14

    h-index

1–5 of 5.8K

Venues

  1. Journal of the American Statistical Association

    136 publications · 29.3K citations

    61

    h-index

  2. The Annals of Statistics

    85 publications · 34K citations

    44

    h-index

  3. Biometrika

    45 publications · 4.6K citations

    26

    h-index

  4. arXiv (Cornell University)

    Repository · 86 publications · 2.6K citations

    26

    h-index

  5. Technometrics

    37 publications · 5.1K citations

    26

    h-index

1–5