Variable Selection

Variable Selection is the statistical process of identifying a subset of predictors from a larger set of potential variables to include in a model based on their relevance to the outcome, balancing model fit and parsimony within the context of Bayesian inference, predictive accuracy, risk factor identification, and inferential validity.

3K

Publications

365.7K

Citations

6.7K

Authors

2.3K

Institutions

Publications per year

2017–2026

956

Authors

6.7K

  1. RL
    Runze Li

    Pennsylvania State University, United States

    21 publications · 13.1K citations

    18

    h-index

  2. JF
    Jianqing Fan

    Princeton University, United States

    16 publications · 13.2K citations

    16

    h-index

  3. EI
    Edward I. George

    University of Pennsylvania, United States

    17 publications · 7K citations

    16

    h-index

  4. YL
    Yi‐Zeng Liang

    Central South University, China

    16 publications · 1.6K citations

    15

    h-index

  5. YW
    Yichao Wu

    North Carolina State University, United States

    12 publications · 691 citations

    12

    h-index

1–5 of 6.7K

Venues

  1. Journal of the American Statistical Association

    115 publications · 37.1K citations

    63

    h-index

  2. Expert Systems with Applications

    74 publications · 7.8K citations

    46

    h-index

  3. Chemometrics and Intelligent Laboratory Systems

    69 publications · 6.9K citations

    36

    h-index

  4. Computational Statistics & Data Analysis

    CSDA · 81 publications · 4.9K citations

    35

    h-index

  5. The Annals of Statistics

    48 publications · 9.8K citations

    35

    h-index

1–5