Semiparametric Functional Modeling

Semiparametric Functional Modeling is a functional regression framework that combines parametric and nonparametric components by modeling the relationship between functional covariates and responses through a finite-dimensional parameter structure while allowing part of the model to remain unspecified and data-determined.

27

Publications

1.5K

Citations

69

Authors

46

Institutions

Publications per year

2017–2026

5

Authors

69

  1. JC
    Jeng‐Min Chiou

    Institute of Statistical Science, Academia Sinica, Taiwan

    2 publications · 156 citations

    2

    h-index

  2. TZ
    Tingting Zhang

    University of Virginia, United States

    1 publications · 12 citations

    1

    h-index

  3. AY
    Adonis Yatchew

    University of Toronto, Canada

    1 publications · 35 citations

    1

    h-index

  4. JS
    Jeffrey S. Morris

    The University of Texas MD Anderson Cancer Center, United States

    1 publications · 23 citations

    1

    h-index

  5. AC
    Antonio Canale

    University of Padua, Italy

    1 publications · 15 citations

    1

    h-index

1–5 of 69

Venues

  1. 3

    h-index

  2. The Annals of Statistics

    2 publications · 391 citations

    2

    h-index

  3. 2

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  4. Journal of Multivariate Analysis

    2 publications · 40 citations

    2

    h-index

  5. Econometric Theory

    1 publications · 30 citations

    1

    h-index

1–5