Jackknife Variance Estimation

Jackknife Variance Estimation is a resampling-based statistical method that belongs to the class of nonparametric variance estimation techniques, distinguished by its systematic omission of one observation at a time from the sample to compute pseudo-values and thereby estimate the variance of a statistic.

272

Publications

46.8K

Citations

449

Authors

249

Institutions

Publications per year

2017–2026

27

Authors

449

  1. JN
    J. N. K. Rao

    Carleton University, Canada

    16 publications · 880 citations

    14

    h-index

  2. JS
    Jun Shao

    University of Wisconsin–Madison, United States

    15 publications · 1K citations

    13

    h-index

  3. RR
    R. R. Sitter

    Simon Fraser University, Canada

    7 publications · 305 citations

    7

    h-index

  4. WR
    William R. Schucany

    Southern Methodist University, United States

    6 publications · 244 citations

    6

    h-index

  5. PS
    Phillip S. Kott

    National Agricultural Statistics Service, United States

    4 publications · 251 citations

    4

    h-index

1–5 of 449

Venues

  1. Journal of the American Statistical Association

    35 publications · 7.2K citations

    25

    h-index

  2. The Annals of Statistics

    22 publications · 23.9K citations

    18

    h-index

  3. Biometrika

    16 publications · 2.1K citations

    12

    h-index

  4. Biometrics

    8 publications · 1.4K citations

    8

    h-index

  5. 8

    h-index

1–5