Huber Estimation

Huber Estimation is a robust statistical method that belongs to the class of M-estimators and is distinguished by its use of a loss function combining quadratic behavior for small residuals with linear behavior for large residuals to reduce the influence of outliers.

149

Publications

10.7K

Citations

279

Authors

166

Institutions

Publications per year

2017–2026

45

Authors

279

  1. WZ
    Wen‐Xin Zhou

    University of California San Diego, United States

    6 publications · 494 citations

    6

    h-index

  2. LM
    Lamine Mili

    Virginia Tech, United States

    5 publications · 229 citations

    5

    h-index

  3. SJ
    Søren Johansen

    University of Copenhagen, Denmark

    4 publications · 274 citations

    4

    h-index

  4. JZ
    Junbo Zhao

    University of Connecticut, United States

    3 publications · 143 citations

    4

    h-index

  5. JF
    Jianqing Fan

    Princeton University, United States

    4 publications · 460 citations

    4

    h-index

1–5 of 279

Venues

  1. Journal of the American Statistical Association

    11 publications · 4.3K citations

    11

    h-index

  2. The Annals of Statistics

    10 publications · 1.1K citations

    11

    h-index

  3. IEEE Transactions on Power Systems

    6 publications · 296 citations

    7

    h-index

  4. Technometrics

    5 publications · 161 citations

    5

    h-index

  5. IEEE Transactions on Signal Processing

    4 publications · 149 citations

    4

    h-index

1–5