Partial Correlation Visualization

Partial Correlation Visualization is a type of correlation visualization that specifically represents the relationship between two variables while statistically controlling for the influence of one or more additional variables, thereby isolating and depicting the unique association between the primary variables of interest.

7

Publications

180

Citations

17

Authors

18

Institutions

Publications per year

2017–2026

3

Authors

17

  1. GT
    Guy Thomas

    University of California San Diego, United States

    1 publications · 11 citations

    1

    h-index

  2. TN
    Tomoki Nakaya

    Tohoku University, Japan

    1 publications · 15 citations

    1

    h-index

  3. SL
    Shaobo Li

    Guizhou University, China

    1 publications · 17 citations

    1

    h-index

  4. RF
    Roland Fried

    TU Dortmund University, Germany

    1 publications · 13 citations

    1

    h-index

  5. GC
    Guadalupe Corcobado

    Estacion Experimental de Zonas Aridas, Spain

    1 publications · 76 citations

    1

    h-index

1–5 of 17

Venues

  1. 1

    h-index

  2. 1

    h-index

  3. Web Ecology

    1 publications · 76 citations

    1

    h-index

  4. Statistics & Probability Letters

    1 publications · 13 citations

    1

    h-index

  5. Journal of Geovisualization and Spatial Analysis

    JGSA · 1 publications · 15 citations

    1

    h-index

1–5