Block Cross-validation

Block Cross-Validation is a temporal cross-validation technique in which data are partitioned into contiguous blocks along a time dimension, preserving temporal dependence by ensuring that training sets precede test sets chronologically to prevent data leakage.

10

Publications

632

Citations

30

Authors

27

Institutions

Publications per year

2017–2026

5

Authors

30

  1. JS
    Jeffrey S. Racine

    McMaster University, Canada

    2 publications · 240 citations

    2

    h-index

  2. FS
    Felix Schiefer

    Karlsruhe Institute of Technology, Germany

    1 publications · 125 citations

    1

    h-index

  3. JS
    Jeffrey S. Spence

    The University of Texas at Dallas, United States

    1 publications · 13 citations

    1

    h-index

  4. AS
    Andy Stock

    Stanford University, United States

    1 publications · 31 citations

    1

    h-index

  5. JL
    Joy Lawrence

    Harvard University, United States

    1 publications · 16 citations

    1

    h-index

1–5 of 30

Venues

  1. 1

    h-index

  2. The Annals of Statistics

    1 publications · 20 citations

    1

    h-index

  3. 1

    h-index

  4. Environment International

    1 publications · 16 citations

    1

    h-index

  5. Journal of Applied Econometrics

    1 publications · 35 citations

    1

    h-index

1–5