Design-based Small Area Estimation

Design-Based Small Area Estimation is a small area estimation approach that relies on the sampling design for inference, distinguishing itself from model-based methods by deriving validity from the randomization distribution induced by the selected probability sampling mechanism.

29

Publications

1.6K

Citations

47

Authors

26

Institutions

Publications per year

2017–2026

3

Authors

47

  1. DP
    Danny Pfeffermann

    Hebrew University of Jerusalem, Israel

    3 publications · 559 citations

    3

    h-index

  2. MG
    Malay Ghosh

    University of Florida, United States

    3 publications · 107 citations

    3

    h-index

  3. DM
    Daniel Mandallaz

    ETH Zurich, Switzerland

    3 publications · 99 citations

    3

    h-index

  4. JN
    J. N. K. Rao

    Carleton University, Canada

    3 publications · 80 citations

    3

    h-index

  5. IM
    Isabel Molina

    Universidad Carlos III de Madrid, Spain

    2 publications · 42 citations

    2

    h-index

1–5 of 47

Venues

  1. Computational Statistics & Data Analysis

    CSDA · 4 publications · 83 citations

    4

    h-index

  2. Statistical Science

    3 publications · 459 citations

    3

    h-index

  3. Test

    3 publications · 423 citations

    3

    h-index

  4. Journal of Official Statistics

    JOS · 2 publications · 40 citations

    2

    h-index

  5. ePrints Soton (University of Southampton)

    Repository · 2 publications · 56 citations

    2

    h-index

1–5