Lag Selection

Lag Selection is a methodological procedure in autocorrelation analysis that determines the optimal number of time lags to include in a model to accurately capture temporal dependencies while avoiding overfitting.

108

Publications

14.9K

Citations

203

Authors

165

Institutions

Publications per year

2017–2026

19

Authors

203

  1. SN
    Serena Ng

    Columbia University, United States

    6 publications · 6.1K citations

    6

    h-index

  2. AH
    Abdulnasser Hatemi‐J

    United Arab Emirates University, United Arab Emirates

    6 publications · 705 citations

    6

    h-index

  3. PP
    Pierre Perrón

    Boston University, United States

    6 publications · 6.1K citations

    6

    h-index

  4. LY
    Lijian Yang

    Michigan State University, United States

    4 publications · 267 citations

    4

    h-index

  5. RS
    R. Scott Hacker

    Jönköping University, Sweden

    3 publications · 178 citations

    3

    h-index

1–5 of 203

Venues

  1. RePEc: Research Papers in Economics

    Repository · 4 publications · 103 citations

    4

    h-index

  2. arXiv (Cornell University)

    Repository · 3 publications · 125 citations

    3

    h-index

  3. Econometric Reviews

    3 publications · 88 citations

    3

    h-index

  4. 3

    h-index

  5. Journal of Time Series Analysis

    3 publications · 366 citations

    3

    h-index

1–5