Regression modelRegression / GLM

Generalized Linear Model (GLM)

The Generalized Linear Model is a unified regression framework that extends ordinary linear regression to outcomes from the exponential family — including binary, count, proportion, and continuous positive outcomes. A link function connects the linear predictor to the mean of the response, enabling principled modelling beyond the Gaussian case.

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Nelder, J. A., & Wedderburn, R. W. M. (1972). Generalized linear models. Journal of the Royal Statistical Society: Series A (General), 135(3), 370–384. DOI: 10.2307/2344614 ↗
McCullagh, P., & Nelder, J. A. (1989). Generalized Linear Models (2nd ed.). Chapman and Hall/CRC. ISBN: 978-0412317606

Referenced by

Bayesian Generalized Linear Model Hierarchical Linear Model Mixed Effects Model Ordinal Logistic Regression Robust Generalized linear model Robust Multinomial Logistic Regression Robust Negative Binomial Regression Robust Poisson Regression Robust Probit Model Zero-inflated model

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