Linear Models

Linear Models is a statistical modeling framework that describes a response variable as a linear combination of predictor variables, distinguished by its assumption of additive linearity in parameters and error structure.

7.9K

Publications

824.2K

Citations

22.1K

Authors

5.2K

Institutions

Publications per year

2017–2026

2K

Variants

Linear Statistical Models

Authors

22.1K

  1. JA
    J. A. Nelder

    Imperial College London, United Kingdom

    20 publications · 7.1K citations

    17

    h-index

  2. JW
    Joseph W. McKean

    Western Michigan University, United States

    14 publications · 884 citations

    13

    h-index

  3. RJ
    Raymond J. Carroll

    Texas A&M University, United States

    13 publications · 983 citations

    12

    h-index

  4. HL
    Hua Liang

    George Washington University, United States

    13 publications · 758 citations

    11

    h-index

  5. FA
    Franklin A. Graybill

    Colorado State University, United States

    11 publications · 2.6K citations

    11

    h-index

1–5 of 22.1K

Venues

  1. Journal of the American Statistical Association

    225 publications · 63.6K citations

    87

    h-index

  2. Technometrics

    110 publications · 53.7K citations

    65

    h-index

  3. Biometrics

    88 publications · 11.8K citations

    48

    h-index

  4. The Annals of Statistics

    84 publications · 9.3K citations

    47

    h-index

  5. Biometrika

    91 publications · 20.7K citations

    47

    h-index

1–5