Identically Distributed Random Variables

Identically Distributed Random Variables is a statistical concept referring to a collection of random variables that share the same probability distribution, thereby differing only in their realization while maintaining identical distributional properties.

512

Publications

34K

Citations

683

Authors

352

Institutions

Publications per year

2017–2026

37

Authors

683

  1. CC
    C. C. Heyde

    Australian National University, Australia

    11 publications · 366 citations

    11

    h-index

  2. IS
    Irina Shevtsova

    Lomonosov Moscow State University, Russia

    6 publications · 334 citations

    6

    h-index

  3. DM
    David M. Mason

    University of Delaware, United States

    5 publications · 249 citations

    5

    h-index

  4. DS
    David Siegmund

    Stanford University, United States

    5 publications · 433 citations

    5

    h-index

  5. JB
    José Blanchet

    Columbia University, United States

    5 publications · 160 citations

    5

    h-index

1–5 of 683

Venues

  1. The Annals of Probability

    40 publications · 2.2K citations

    23

    h-index

  2. Theory of Probability and Its Applications

    42 publications · 1.2K citations

    22

    h-index

  3. Journal of Applied Probability

    JAP · 40 publications · 1.3K citations

    21

    h-index

  4. The Annals of Mathematical Statistics

    30 publications · 12.4K citations

    20

    h-index

  5. The Annals of Statistics

    25 publications · 1.8K citations

    20

    h-index

1–5