Bootstrap Resampling Weights

Bootstrap Resampling Weights is a statistical construct that assigns observation-specific multinomial sampling weights to individual data points in a bootstrap sample, reflecting their frequency of selection in a resampling-with-replacement procedure, thereby quantifying the contribution of each original observation to a given bootstrap replicate.

21

Publications

1.1K

Citations

49

Authors

34

Institutions

Publications per year

2017–2026

2

Authors

49

  1. ÉR
    Étienne Roquain

    Laboratoire de Probabilités et Modèles Aléatoires, France

    2 publications · 63 citations

    2

    h-index

  2. RM
    Richard M. Durand

    Auburn University, United States

    2 publications · 79 citations

    2

    h-index

  3. ZV
    Zarrel V. Lambert

    University of Florida, United States

    2 publications · 79 citations

    2

    h-index

  4. GB
    Gilles Blanchard

    University of Potsdam, Germany

    2 publications · 63 citations

    2

    h-index

  5. AR
    Albert R. Wildt

    University of Missouri, United States

    2 publications · 79 citations

    2

    h-index

1–5 of 49

Venues

  1. The Annals of Statistics

    4 publications · 211 citations

    4

    h-index

  2. Journal of Marketing Research

    2 publications · 79 citations

    2

    h-index

  3. Scandinavian Journal of Statistics

    2 publications · 45 citations

    2

    h-index

  4. Journal of Computational and Graphical Statistics

    JCGS · 1 publications · 45 citations

    1

    h-index

  5. The Annals of Applied Statistics

    AOAS · 1 publications · 21 citations

    1

    h-index

1–5