Generalized Linear Models

Ludwig Fahrmeir, Thomas Kneib, Stefan Lang and Brian Marx
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Ludwig Fahrmeir: University of Munich, Department of Statistics
Thomas Kneib: University of Göttingen, Chair of Statistics
Stefan Lang: University of Innsbruck, Department of Statistics
Brian Marx: Louisiana State University, Experimental Statistics

Chapter 5 in Regression, 2013, pp 269-324 from Springer

Abstract: Abstract Linear models are well suited for regression analyses when the response variable is continuous and at least approximately normal. In some cases, an appropriate transformation is needed to ensure approximate normality of the response. In addition, the expectation of the response is assumed to be a linear combination of covariates. Again, these covariates may be transformed before being included in the linear predictor.

Keywords: Score Function; Probit Model; Exponential Family; Linear Predictor; Binary Response Variable (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-34333-9_5

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DOI: 10.1007/978-3-642-34333-9_5

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