Nonlinear Hierarchical Models

Nonlinear Hierarchical Models is a statistical modeling framework that belongs to the class of hierarchical models and is distinguished by its specification of nonlinear functional relationships at multiple levels of data organization to account for complex dependencies and variability across nested or grouped structures.

76

Publications

7.2K

Citations

209

Authors

117

Institutions

Publications per year

2017–2026

13

Variants

Nonlinear Hierarchical Modeling

Authors

209

  1. HV
    Harri Valpola

    Aalto University, Finland

    4 publications · 91 citations

    4

    h-index

  2. JK
    Juha Karhunen

    Helsinki Institute for Information Technology, Finland

    4 publications · 91 citations

    4

    h-index

  3. NR
    Noam Ross

    EcoHealth Alliance, United States

    3 publications · 1.2K citations

    3

    h-index

  4. GL
    Gavin L. Simpson

    University of Regina, Canada

    3 publications · 1.2K citations

    3

    h-index

  5. EJ
    Eric J. Pedersen

    Fisheries and Oceans Canada, Canada

    3 publications · 1.2K citations

    3

    h-index

1–5 of 209

Venues

  1. Biometrics

    3 publications · 355 citations

    3

    h-index

  2. Journal of the American Statistical Association

    3 publications · 1.4K citations

    3

    h-index

  3. arXiv (Cornell University)

    Repository · 2 publications · 74 citations

    2

    h-index

  4. Technometrics

    2 publications · 816 citations

    2

    h-index

  5. PLoS Computational Biology

    1 publications · 90 citations

    1

    h-index

1–5