Distribution Visualization

Distribution Visualization is a form of uncertainty visualization that specifically represents the probabilistic spread or likelihood of data values across a continuous range, distinguished by its focus on depicting complete probability distributions rather than summary statistics or discrete uncertainty intervals.

101

Publications

8.4K

Citations

224

Authors

120

Institutions

Publications per year

2017–2026

25

Authors

224

  1. AP
    Alex Pang

    University of California, Santa Cruz, United States

    4 publications · 149 citations

    4

    h-index

  2. DK
    David Kao

    University of Colorado Denver, United States

    3 publications · 121 citations

    3

    h-index

  3. JD
    Jennifer Dungan

    Ames Research Center, United States

    3 publications · 98 citations

    3

    h-index

  4. HH
    Heike Hofmann

    Iowa State University, United States

    3 publications · 379 citations

    3

    h-index

  5. EV
    Ellen Vandervieren

    University of Antwerp, Belgium

    2 publications · 51 citations

    2

    h-index

1–5 of 224

Venues

  1. The American Statistician

    9 publications · 274 citations

    9

    h-index

  2. Journal of Computational and Graphical Statistics

    JCGS · 6 publications · 770 citations

    6

    h-index

  3. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 5 publications · 318 citations

    5

    h-index

  4. Journal of Statistical Software

    JSS · 3 publications · 846 citations

    3

    h-index

  5. Biometrika

    3 publications · 1.2K citations

    3

    h-index

1–5