Graphical Log-linear Models

Graphical Log-Linear Models is a class of probabilistic models for categorical data that belongs to the family of log-linear models and is distinguished by its incorporation of conditional independence structures represented via undirected graphs, where nodes correspond to variables and edges encode direct associations.

73

Publications

5.8K

Citations

157

Authors

90

Institutions

Publications per year

2017–2026

6

Variants

Log-linear Graphical Models

Authors

157

  1. SK
    Svend Kreiner

    University of Copenhagen, Denmark

    3 publications · 94 citations

    3

    h-index

  2. PW
    Paul W. Holland

    Educational Testing Service, United States

    3 publications · 177 citations

    3

    h-index

  3. DT
    Dorothy T. Thayer

    Educational Testing Service, United States

    3 publications · 177 citations

    3

    h-index

  4. JC
    Jukka Corander

    University of Helsinki, Finland

    2 publications · 36 citations

    2

    h-index

  5. LA
    Leonard A. Marascuilo

    University of California, Berkeley, United States

    2 publications · 77 citations

    2

    h-index

1–5 of 157

Venues

  1. Biometrika

    5 publications · 395 citations

    5

    h-index

  2. 5

    h-index

  3. 3

    h-index

  4. 3

    h-index

  5. The Annals of Statistics

    2 publications · 235 citations

    2

    h-index

1–5