Robust Variable Selection

Robust Variable Selection is a statistical methodology that identifies relevant predictors in a regression model while maintaining reliability and stability under violations of standard assumptions, such as the presence of outliers, heavy-tailed errors, or influential observations.

142

Publications

8.7K

Citations

410

Authors

259

Institutions

Publications per year

2017–2026

51

Authors

410

  1. ZZ
    Zhongyi Zhu

    Fudan University, China

    3 publications · 83 citations

    3

    h-index

  2. HY
    Hu Yang

    Chongqing University, China

    3 publications · 80 citations

    3

    h-index

  3. YS
    Yunquan Song

    China University of Petroleum, East China, China

    3 publications · 75 citations

    3

    h-index

  4. JS
    Jun S. Liu

    Harvard University, United States

    3 publications · 75 citations

    3

    h-index

  5. KW
    Kangning Wang

    Shandong Institute of Business and Technology, China

    3 publications · 64 citations

    3

    h-index

1–5 of 410

Venues

  1. Computational Statistics & Data Analysis

    CSDA · 12 publications · 512 citations

    12

    h-index

  2. Journal of Multivariate Analysis

    7 publications · 195 citations

    7

    h-index

  3. 6

    h-index

  4. Biometrics

    5 publications · 222 citations

    5

    h-index

  5. Analytica Chimica Acta

    5 publications · 355 citations

    5

    h-index

1–5