Horvitz-thompson Estimation

Horvitz-Thompson Estimation is a statistical method in sampling theory that belongs to the class of weighted estimators, distinguished by its use of inverse selection probabilities to produce unbiased estimates of population totals under unequal probability sampling schemes.

148

Publications

6.7K

Citations

264

Authors

151

Institutions

Publications per year

2017–2026

20

Variants

Horvitz-thompson Estimator

Authors

264

  1. LF
    Lorenzo Fattorini

    University of Siena, Italy

    5 publications · 164 citations

    5

    h-index

  2. AG
    Anton Grafström

    Swedish University of Agricultural Sciences, Sweden

    5 publications · 369 citations

    5

    h-index

  3. WS
    W. Scott Overton

    Oregon State University, United States

    4 publications · 151 citations

    4

    h-index

  4. SV
    Stephen V. Stehman

    SUNY College of Environmental Science and Forestry, United States

    4 publications · 151 citations

    4

    h-index

  5. JU
    Johan Ugander

    Stanford University, United States

    3 publications · 248 citations

    3

    h-index

1–5 of 264

Venues

  1. Journal of the American Statistical Association

    18 publications · 741 citations

    14

    h-index

  2. The Annals of Statistics

    9 publications · 205 citations

    10

    h-index

  3. Biometrics

    8 publications · 371 citations

    8

    h-index

  4. Environmetrics

    7 publications · 552 citations

    7

    h-index

  5. Biometrika

    6 publications · 684 citations

    6

    h-index

1–5