State-space Causal Models

State-Space Causal Models is a longitudinal causal inference framework that integrates state-space modeling with causal structure to distinguish latent temporal dynamics from causal interventions in time-series observational data.

11

Publications

1.4K

Citations

27

Authors

21

Institutions

Publications per year

2017–2026

4

Authors

27

  1. LA
    Laura Astolfi

    Sapienza University of Rome, Italy

    1 publications · 16 citations

    1

    h-index

  2. JL
    Jiuyong Li

    University of South Australia, Australia

    1 publications · 36 citations

    1

    h-index

  3. SL
    Steven L. Scott

    University of Wisconsin–Madison, United States

    1 publications · 962 citations

    1

    h-index

  4. HW
    Halbert White

    University of California San Diego, United States

    1 publications · 11 citations

    1

    h-index

  5. KJ
    Kristopher J. Preacher

    Vanderbilt University, United States

    1 publications · 29 citations

    1

    h-index

1–5 of 27

Venues

  1. Physical Review E

    PRE · 2 publications · 275 citations

    2

    h-index

  2. Transport Policy

    1 publications · 16 citations

    1

    h-index

  3. The Annals of Applied Statistics

    AOAS · 1 publications · 962 citations

    1

    h-index

  4. Pattern Recognition Letters

    1 publications · 36 citations

    1

    h-index

  5. Biological Cybernetics

    1 publications · 11 citations

    1

    h-index

1–5