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.
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Residuals and Influence in Regression.
Anthony C. Atkinson, R. Dennis Cook, Sanford Weisberg · Biometrics · 1983 · 1.9K citations
Checking the Cox model with cumulative sums of martingale-based residuals
D. Y. Lin, L. J. Wei, Z. Ying · Biometrika · 1993 · 1.4K citations
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Universidade de São Paulo
São Paulo, Brazil
12 h-index
33 publications
1.3K citations

UNSW Sydney
Sydney, Australia
10 h-index
15 publications
1.2K citations
University of California, Los Angeles
Los Angeles, United States
10 h-index
16 publications
389 citations

Pennsylvania State University
State College, United States
9 h-index
10 publications
527 citations

University of Minnesota
Minneapolis, United States
9 h-index
15 publications
7.6K citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
8 h-index
13 publications
1.3K citations

Chinese Academy of Sciences
Beijing, China
8 h-index
21 publications
1K citations
Princeton University
Princeton, United States
7 h-index
13 publications
3.9K citations
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BSSA · 10 publications · 337 citations
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