Empirical Cumulative Distribution Function

An Empirical Cumulative Distribution Function is a non-parametric estimator of the cumulative distribution function of a random variable, defined as the step function that jumps by \( \frac{1}{n} \) at each observed data point, thereby representing the proportion of observations less than or equal to a given value in a finite sample.

455

Publications

26.5K

Citations

997

Authors

543

Institutions

Publications per year

2017–2026

97

Variants

EcdfEmpirical Distribution Function

Authors

997

  1. PR
    Pál Révész

    Hungarian Academy of Sciences, Hungary

    4 publications · 104 citations

    4

    h-index

  2. SN
    Soumendra N. Lahiri

    Iowa State University, United States

    4 publications · 139 citations

    4

    h-index

  3. NC
    Noel Cressie

    Iowa State University, United States

    3 publications · 127 citations

    3

    h-index

  4. RO
    Richard O. Buckius

    University of Illinois Urbana-Champaign, United States

    3 publications · 68 citations

    3

    h-index

  5. NH
    Nan‐Jung Hsu

    National Tsing Hua University, Taiwan

    3 publications · 127 citations

    3

    h-index

1–5 of 997

Venues

  1. Journal of the American Statistical Association

    22 publications · 2.2K citations

    19

    h-index

  2. The Annals of Mathematical Statistics

    19 publications · 6K citations

    16

    h-index

  3. The Annals of Statistics

    16 publications · 1.3K citations

    13

    h-index

  4. Biometrika

    10 publications · 654 citations

    10

    h-index

  5. Communication in Statistics- Theory and Methods

    10 publications · 350 citations

    10

    h-index

1–5