Residual Analysis

Residual Analysis is a diagnostic procedure in statistical modeling that examines the differences between observed values and the values predicted by a model, particularly within the framework of Generalized Linear Models, to assess model adequacy, detect violations of assumptions, and identify influential observations for the purpose of Bayesian Model Checking, Error Analysis, and Model Validation.

654

Publications

54.1K

Citations

1.7K

Authors

756

Institutions

Publications per year

2017–2026

151

Authors

1.7K

  1. EM
    Edwin M. M. Ortega

    Universidade de São Paulo, Brazil

    8 publications · 224 citations

    8

    h-index

  2. GA
    Gilberto A. Paula

    Universidade de São Paulo, Brazil

    6 publications · 216 citations

    6

    h-index

  3. SJ
    Simon J. Sheather

    UNSW Sydney, Australia

    5 publications · 142 citations

    5

    h-index

  4. JW
    Joseph W. McKean

    Western Michigan University, United States

    5 publications · 142 citations

    5

    h-index

  5. EA
    Emrah Altun

    Bartin University, Türkiye

    5 publications · 228 citations

    5

    h-index

1–5 of 1.7K

Venues

  1. Journal of the American Statistical Association

    27 publications · 5.6K citations

    20

    h-index

  2. Technometrics

    21 publications · 3.1K citations

    17

    h-index

  3. Biometrika

    17 publications · 2.5K citations

    15

    h-index

  4. Biometrics

    11 publications · 3.7K citations

    11

    h-index

  5. Bulletin of the Seismological Society of America

    BSSA · 10 publications · 337 citations

    10

    h-index

1–5