Cumulative Distribution Function Comparisons

Cumulative Distribution Function Comparisons is a methodological framework in the theory of stochastic dominance that evaluates and ranks random outcomes by systematically comparing the cumulative distribution functions of probability distributions to determine dominance relationships based on their relative shift and spread.

38

Publications

2.3K

Citations

109

Authors

74

Institutions

Publications per year

2017–2026

11

Authors

109

  1. RL
    Raul Lopes

    Brunel University of London, United Kingdom

    2 publications · 148 citations

    2

    h-index

  2. TO
    Tomoaki Ohtsuki

    Keio University, Japan

    1 publications · 39 citations

    1

    h-index

  3. CN
    Christopher Nimsky

    Philipps University of Marburg, Germany

    1 publications · 14 citations

    1

    h-index

  4. AI
    Atsushi Ishii

    Fukuoka University, Japan

    1 publications · 19 citations

    1

    h-index

  5. LF
    Longxiang Fang

    Anhui Normal University, China

    1 publications · 26 citations

    1

    h-index

1–5 of 109

Venues

  1. The Annals of Mathematical Statistics

    3 publications · 54 citations

    3

    h-index

  2. 1

    h-index

  3. Journal of the Korean Statistical Society

    1 publications · 26 citations

    1

    h-index

  4. ICES Journal of Marine Science

    1 publications · 67 citations

    1

    h-index

  5. Journal of Applied Meteorology and Climatology

    JAMC · 1 publications · 21 citations

    1

    h-index

1–5