Sample Autocorrelation

Sample Autocorrelation is a statistical estimator that quantifies the degree of linear dependence between observations of a time series separated by a specific lag, derived from finite empirical data as the sample-level counterpart to the theoretical autocorrelation function.

127

Publications

11.5K

Citations

219

Authors

141

Institutions

Publications per year

2017–2026

11

Variants

Sacf

Authors

219

  1. TM
    Thomas Mikosch

    University of Copenhagen, Denmark

    4 publications · 718 citations

    4

    h-index

  2. DA
    David A. Pierce

    Federal Reserve, United States

    4 publications · 4.3K citations

    4

    h-index

  3. RA
    Richard A. Davis

    Colorado State University, United States

    4 publications · 851 citations

    4

    h-index

  4. GS
    Gennady Samorodnitsky

    Cornell University, United States

    3 publications · 63 citations

    3

    h-index

  5. HH
    Hossein Hassani

    University of Tehran, Iran

    3 publications · 73 citations

    3

    h-index

1–5 of 219

Venues

  1. Journal of the American Statistical Association

    14 publications · 5.9K citations

    13

    h-index

  2. Journal of Time Series Analysis

    6 publications · 204 citations

    6

    h-index

  3. Biometrika

    6 publications · 359 citations

    6

    h-index

  4. Journal of Econometrics

    5 publications · 435 citations

    5

    h-index

  5. Econometric Theory

    3 publications · 133 citations

    3

    h-index

1–5