Generalized Linear Models

McCullagh, P., & Nelder, J. A. (1989). Generalized Linear Models. Chapman & Hall.

Type

Book

Intellectual base

Review or monograph

Year

1989

DOI

10.1007/978-1-4899-3242-6

ISBN

9780412317606

Link

https://doi.org/10.1007/978-1-4899-3242-6

Cited from

statistics_experimental_design

Cited by

3 citations across 3 artifacts.

Primes

• Distributional Assumption
  • The distributional assumption is part of the specification but not synonymous with it, as McCullagh and Nelder (1989) make explicit in decomposing generalized linear models into random component, systematic component, and link function.

Domain-specific

• Binomial regression
  • Binomial regression models a count \(Y_i\) with \(Y_i ∼ Binomial(n_i,p_i)\) and relates its success probability to predictors through a link such as \(g(p_i) = x_i^Tβ\).
• Variance function
  • A wrong variance function misstates precision even when the linear predictor for the mean is correctly specified.

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