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Published in:
2000 | OriginalPaper | Chapter
Generalized Linear Models
Author : Marlene Müller
Published in: XploRe — Learning Guide
Publisher: Springer Berlin Heidelberg
Included in: Professional Book Archive
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McCullagh and Nelder (1989) summarized many approaches to relax the distributional assumptions of the classical linear model under the common term Generalized Linear Models (GLM). A generalized linear model (GLM) is a regression model of the form$$EY = G({x^T}\beta ),$$where EY denotes the expected value of the dependent variable Y, x is a vector of explanatory variables, β an unknown parameter vector and G(•) a known link function.