Predictive Model Selection

Predictive Model Selection is a model selection paradigm that belongs to the class of statistical model evaluation methods, distinguished by its focus on choosing models based on their out-of-sample predictive performance for categorical outcomes rather than goodness-of-fit or theoretical optimality criteria.

441

Publications

65.1K

Citations

1.3K

Authors

624

Institutions

Publications per year

2017–2026

112

Authors

1.3K

  1. AV
    Aki Vehtari

    Aalto University, Finland

    6 publications · 792 citations

    6

    h-index

  2. PW
    Purushottam W. Laud

    Medical College of Wisconsin, United States

    5 publications · 557 citations

    5

    h-index

  3. YY
    Yuhong Yang

    University of Minnesota, United States

    4 publications · 471 citations

    4

    h-index

  4. DM
    David M. Allen

    University of Kentucky, United States

    4 publications · 2.5K citations

    4

    h-index

  5. PL
    Peter L. Bartlett

    University of California, Berkeley, United States

    4 publications · 421 citations

    4

    h-index

1–5 of 1.3K

Venues

  1. Journal of the American Statistical Association

    18 publications · 4.3K citations

    17

    h-index

  2. Technometrics

    11 publications · 9.1K citations

    11

    h-index

  3. Journal of Chemometrics

    11 publications · 2K citations

    11

    h-index

  4. Journal of Statistical Planning and Inference

    10 publications · 295 citations

    10

    h-index

  5. arXiv (Cornell University)

    Repository · 9 publications · 1.4K citations

    9

    h-index

1–5