Bootstrap Confidence Intervals

Bootstrap Confidence Intervals is a statistical method for estimating the sampling distribution of a parameter by resampling with replacement from observed data, thereby constructing confidence intervals without relying on parametric assumptions.

1.7K

Publications

183.3K

Citations

3.5K

Authors

1.5K

Institutions

Publications per year

2017–2026

346

Variants

Bootstrap Cis

Authors

3.5K

  1. PH
    Peter Hall

    Australian National University, Australia

    29 publications · 2.4K citations

    24

    h-index

  2. BE
    Bradley Efron

    Stanford University, United States

    26 publications · 10.1K citations

    23

    h-index

  3. DN
    Dimitris N. Politis

    University of California San Diego, United States

    14 publications · 3.7K citations

    14

    h-index

  4. JP
    Joseph P. Romano

    Stanford University, United States

    13 publications · 3.9K citations

    12

    h-index

  5. SD
    Sanku Dey

    Zagazig University, Egypt

    12 publications · 368 citations

    12

    h-index

1–5 of 3.5K

Venues

  1. Journal of the American Statistical Association

    72 publications · 15.7K citations

    44

    h-index

  2. Statistics in Medicine

    63 publications · 8K citations

    37

    h-index

  3. The Annals of Statistics

    48 publications · 6.5K citations

    33

    h-index

  4. Biometrika

    33 publications · 3.7K citations

    22

    h-index

  5. Biometrics

    26 publications · 1.8K citations

    21

    h-index

1–5