Generalized Linear Model Theory is a theoretical framework within statistical modeling that extends the linear regression paradigm by specifying a distribution from the exponential family and a link function to relate the linear predictor to the mean of the response variable.
1.7K
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1.9K
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Publications per year
2017–2026
473
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Glm Theory
Parents
Publications
1.7K
Applied Linear Statistical Models
Eric R. Ziegel, John Neter, William Wasserman et al. · Technometrics · 1992 · 10K citations
Applied Linear Statistical Models
Michael Kutner · Technometrics · 1997 · 7.3K citations · Full text
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- RJ
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1.9K
Harvard University
Cambridge, United States
18 h-index
48 publications
5.9K citations
Johns Hopkins University
Baltimore, United States
16 h-index
42 publications
4.2K citations
University of Wisconsin–Madison
Madison, United States
16 h-index
35 publications
2.4K citations
Imperial College London
London, United Kingdom
16 h-index
27 publications
1.8K citations
Virginia Tech
Blacksburg, United States
15 h-index
23 publications
1K citations
University of Washington
Seattle, United States
15 h-index
31 publications
7K citations
Texas A&M University
College Station, United States
15 h-index
35 publications
2.3K citations
Cornell University
Ithaca, United States
14 h-index
20 publications
3K citations
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- Journal of the American Statistical Association
86 publications · 28.2K citations
48
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- Technometrics
58 publications · 32.9K citations
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- Biometrics
41 publications · 4.2K citations
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- Biometrika
29 publications · 5.9K citations
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- PLoS ONE
37 publications · 1.4K citations
24
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