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A generalization of linear regression allowing for nonlinear relationships via a "link function" and for the variance of the response to depend on the predicted value. (Not to be confused with "general linear model" which extends the ordinary linear model to general covariance structure and multivariate response.)

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If we do a negative binomial GLM with unknown deviance, a frequent strategy (used for example by glm.nb in package MASS in R) is to use a Gibbs sampler: Hold dispersion fixed, estimate the mean Hold …
asked Sep 13 '16 by yannick
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It's not the same but it can be close. In this example, offset and exponent are less than $10^{-3}$ apart between the poisson and negative binomial estimate. The Poisson dispersion estimate is 1.08, w …
answered Sep 14 '16 by yannick