Holdout Sample Evaluation

Holdout Sample Evaluation is a validation technique in revenue forecasting research that belongs to the broader class of out-of-sample evaluation methods, distinguished by its use of a temporally or randomly partitioned subset of observed data withheld from model training to provide an unbiased assessment of predictive accuracy.

32

Publications

5.8K

Citations

72

Authors

45

Institutions

Publications per year

2017–2026

7

Variants

Hold-out Sample Evaluation

Authors

72

  1. BS
    Brian Schwartz

    Universität Trier, Germany

    2 publications · 85 citations

    2

    h-index

  2. EA
    Edgar A. Pessemier

    Purdue University West Lafayette, United States

    2 publications · 52 citations

    2

    h-index

  3. RK
    Rajendra K. Srivastava

    The University of Texas at Austin, United States

    2 publications · 170 citations

    2

    h-index

  4. JG
    Julia Giesemann

    Universität Trier, Germany

    2 publications · 85 citations

    2

    h-index

  5. PA
    Peter A. Creed

    Griffith University, Australia

    2 publications · 43 citations

    2

    h-index

1–5 of 72

Venues

  1. Journal of Marketing Research

    4 publications · 222 citations

    4

    h-index

  2. Journal of Forensic Sciences

    JOFS · 2 publications · 44 citations

    2

    h-index

  3. Managerial Finance

    1 publications · 191 citations

    1

    h-index

  4. The Journal of Finance

    1 publications · 310 citations

    1

    h-index

  5. Management Science

    1 publications · 77 citations

    1

    h-index

1–5