Transcription of glm — Generalized linear models - Stata
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Title glm Generalized linear models Description Quick start Menu Syntax Options Remarks and examples Stored results Methods and formulas Acknowledgments References Also see Description glm fits Generalized linear models . It can fit models by using either IRLS (maximum quasilikelihood). or Newton Raphson (maximum likelihood) optimization, which is the default. See [U] 27 Overview of Stata estimation commands for a description of all of Stata 's estimation commands, several of which fit models that can also be fit using glm. Quick start model of y as a function of x when y is a proportion glm y x, family(binomial). Logit model of y events occurring in 15 trials as a function of x glm y x, family(binomial 15) link(logit).
6glm— Generalized linear models General use glm fits generalized linear models of ywith covariates x: g E(y) = x , y˘F g() is called the link function, and F is the distributional family. Substituting various definitions for g() and F results in a surprising array of models. For instance, if yis distributed as Gaussian
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