Bootstrap Bias Estimation

Bootstrap Bias Estimation is a resampling-based statistical method that quantifies the systematic deviation between a sample estimator and its population parameter by comparing the mean of bootstrap replications to the original sample estimate.

264

Publications

39.9K

Citations

477

Authors

304

Institutions

Publications per year

2017–2026

38

Authors

477

  1. PH
    Peter Hall

    Australian National University, Australia

    10 publications · 1.4K citations

    10

    h-index

  2. PH
    Peter Hall

    Australian National University, Australia

    5 publications · 215 citations

    5

    h-index

  3. JL
    Joël L. Horowitz

    University of Iowa, United States

    5 publications · 994 citations

    5

    h-index

  4. DE
    David E. A. Giles

    University of Victoria, Canada

    4 publications · 145 citations

    4

    h-index

  5. BE
    Bradley Efron

    Stanford University, United States

    4 publications · 3K citations

    4

    h-index

1–5 of 477

Venues

  1. The Annals of Statistics

    15 publications · 3.2K citations

    15

    h-index

  2. Biometrika

    17 publications · 1.4K citations

    14

    h-index

  3. Journal of the American Statistical Association

    13 publications · 3.8K citations

    12

    h-index

  4. 9

    h-index

  5. Journal of Statistical Computation and Simulation

    JSCS · 9 publications · 417 citations

    9

    h-index

1–5