Robust Regression

Robust Regression is a regression method that minimizes the influence of outliers and violations of classical assumptions by employing estimation techniques more resistant to deviations from normality, heteroscedasticity, and data contamination compared to ordinary least squares regression.

1.9K

Publications

183.4K

Citations

4.5K

Authors

1.8K

Institutions

Publications per year

2017–2026

543

Authors

4.5K

  1. PJ
    Peter J. Rousseeuw

    University of Antwerp, Belgium

    26 publications · 20.6K citations

    22

    h-index

  2. RJ
    Raymond J. Carroll

    Texas A&M University, United States

    19 publications · 2.6K citations

    17

    h-index

  3. DR
    David Ruppert

    Cornell University, United States

    14 publications · 6.4K citations

    14

    h-index

  4. SG
    Salvatore Greco

    University of Catania, Italy

    14 publications · 1.2K citations

    14

    h-index

  5. RS
    Roman Słowiński

    Poznań University of Technology, Poland

    14 publications · 1.2K citations

    14

    h-index

1–5 of 4.5K

Venues

  1. Journal of the American Statistical Association

    81 publications · 41.5K citations

    47

    h-index

  2. Technometrics

    49 publications · 14.5K citations

    30

    h-index

  3. The Annals of Statistics

    39 publications · 7.6K citations

    28

    h-index

  4. Computational Statistics & Data Analysis

    CSDA · 36 publications · 1.1K citations

    21

    h-index

  5. 19

    h-index

1–5