In statistics, a generalized linear model (GLM) is a flexible generalization of ordinary linear regression. The GLM generalizes linear regression by allowing...

In statistics, a generalized linear mixed model (GLMM) is an extension to the generalized linear model (GLM) in which the linear predictor contains random...

McCullagh, P.; Nelder, J. A. (1989), "An outline of generalized linear models", Generalized Linear Models, Springer US, pp. 21–47, doi:10.1007/978-1-4899-3242-6_2...

In statistics, a generalized additive model (GAM) is a generalized linear model in which the linear response variable depends linearly on unknown smooth...

hierarchical generalized linear models extend generalized linear models by relaxing the assumption that error components are independent. This allows models to...

"linear model" is not usually applied. One example of this is nonlinear dimensionality reduction. General linear model Generalized linear model Linear...

regression using similar techniques. When viewed in the generalized linear model framework, the probit model employs a probit link function. It is most often...

regression for contingency tables, a type of generalized linear model. The specific applications of log-linear models are where the output quantity lies in the...

discuss mainly linear mixed-effects models rather than generalized linear mixed models or nonlinear mixed-effects models. Linear mixed models (LMMs) are statistical...

statistics, the generalized linear array model (GLAM) is used for analyzing data sets with array structures. It based on the generalized linear model with the...