Semiparametric Modeling

Semiparametric Modeling is a statistical modeling approach that combines a parametric component specifying part of the data structure with a nonparametric component allowing unspecified functional forms, thereby differentiating it from fully parametric and purely nonparametric models.

1.8K

Publications

128.4K

Citations

2.2K

Authors

1.1K

Institutions

Publications per year

2017–2026

213

Authors

2.2K

  1. RJ
    Raymond J. Carroll

    Texas A&M University, United States

    32 publications · 2.3K citations

    24

    h-index

  2. JM
    James M. Robins

    Harvard University, United States

    23 publications · 4K citations

    20

    h-index

  3. OL
    Oliver Linton

    University of Cambridge, United Kingdom

    19 publications · 1.7K citations

    18

    h-index

  4. WK
    Wolfgang Karl Härdle

    Humboldt-Universität zu Berlin, Germany

    21 publications · 1.9K citations

    17

    h-index

  5. JL
    Joël L. Horowitz

    University of Iowa, United States

    17 publications · 2K citations

    16

    h-index

1–5 of 2.2K

Venues

  1. Journal of the American Statistical Association

    140 publications · 16.7K citations

    66

    h-index

  2. Journal of Econometrics

    109 publications · 10.5K citations

    51

    h-index

  3. The Annals of Statistics

    89 publications · 9.3K citations

    49

    h-index

  4. Biometrika

    79 publications · 7.4K citations

    43

    h-index

  5. Econometrica

    41 publications · 10.2K citations

    35

    h-index

1–5