Model Averaging

Model Averaging is an ensemble method that combines predictions from multiple models by computing a weighted or unweighted average, thereby reducing variance and improving generalization through the aggregation of diverse model outputs.

838

Publications

91.5K

Citations

2.2K

Authors

1K

Institutions

Publications per year

2017–2026

299

Authors

2.2K

  1. XZ
    Xinyu Zhang

    Chinese Academy of Sciences, China

    32 publications · 2.1K citations

    22

    h-index

  2. AE
    Adrian E. Raftery

    University of Washington, United States

    17 publications · 8.4K citations

    16

    h-index

  3. GZ
    Guohua Zou

    Chinese Academy of Sciences, China

    15 publications · 1.4K citations

    13

    h-index

  4. AT
    Alan T. K. Wan

    City University of Hong Kong, Hong Kong SAR China

    12 publications · 1.1K citations

    12

    h-index

  5. TS
    Theo S. Eicher

    University of Washington, United States

    9 publications · 532 citations

    9

    h-index

1–5 of 2.2K

Venues

  1. Journal of the American Statistical Association

    23 publications · 3.6K citations

    22

    h-index

  2. SSRN Electronic Journal

    Repository · 36 publications · 1.1K citations

    22

    h-index

  3. arXiv (Cornell University)

    Repository · 20 publications · 6K citations

    15

    h-index

  4. Journal of Econometrics

    14 publications · 1.5K citations

    14

    h-index

  5. Water Resources Research

    10 publications · 859 citations

    10

    h-index

1–5