Generalized Linear Models and Extensions - Fourth Edition Hardin James W. University of South Carolina Columbia USAPaperback / softback

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Generalized linear models (GLMs) extend linear regression to models with a non-Gaussian, or even discrete, response. Although one can fit these models in Stata by using specialized commands (for example, logit for logit models), fitting them as GLMs with Stata's glm command… Celý popis ↓

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Popis Generalized Linear Models and Extensions - Fourth Edition Hardin James W. University of South Carolina Columbia USAPaperback / softback

Generalized Linear Models and Extensions - Fourth Edition Hardin James W. University of South Carolina Columbia USAPaperback / softback

Generalized linear models (GLMs) extend linear regression to models with a non-Gaussian, or even discrete, response. Although one can fit these models in Stata by using specialized commands (for example, logit for logit models), fitting them as GLMs with Stata's glm command offers some advantages. GLM theory is predicated on the exponential family of distributions--a class so rich that it includes the commonly used logit, probit, and Poisson models.

The theory consists of showing how the various GLMs are special cases of the exponential family, showing general properties of this family of distributions, and showing the derivation of maximum likelihood (ML) For example, model diagnostics may be calculated and interpreted similarly regardless of the assumed distribution.This text thoroughly covers GLMs, both theoretically and computationally, with an emphasis on Stata.

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