Regression-based Bias Correction

Regression-Based Bias Correction is a bias correction method that uses regression modeling to estimate and adjust systematic errors in observed data by predicting true values based on biased measurements and auxiliary variables.

113

Publications

12.2K

Citations

267

Authors

175

Institutions

Publications per year

2017–2026

16

Authors

267

  1. GM
    Gauss M. Cordeiro

    Universidade Federal de Pernambuco, Brazil

    5 publications · 516 citations

    5

    h-index

  2. WS
    William Stout

    University of Illinois Urbana-Champaign, United States

    3 publications · 96 citations

    3

    h-index

  3. EP
    Edward P. Lazear

    Stanford University, United States

    2 publications · 216 citations

    2

    h-index

  4. CF
    Chris Frost

    London School of Hygiene & Tropical Medicine, United Kingdom

    2 publications · 350 citations

    2

    h-index

  5. SZ
    Shou Zheng Tang

    Chinese Academy of Forestry, China

    2 publications · 67 citations

    2

    h-index

1–5 of 267

Venues

  1. Statistics & Probability Letters

    4 publications · 221 citations

    4

    h-index

  2. Journal of Statistical Planning and Inference

    4 publications · 71 citations

    4

    h-index

  3. Statistics in Medicine

    3 publications · 79 citations

    3

    h-index

  4. 3

    h-index

  5. 3

    h-index

1–5