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.

Apply with StatMindSoonVideoSoon

Read the full method

Members only

Sign in with a free account to read this section.

Sign in

Sources

  1. 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
  2. McCullagh, P., & Nelder, J. A. (1989). Generalized Linear Models (2nd ed.). Chapman and Hall/CRC. ISBN: 978-0412317606

Related methods

Referenced by

ScholarGateGeneralized Linear Model (Generalized Linear Model). Retrieved 2026-06-04 from https://scholargate.app/en/statistics/generalized-linear-model