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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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What are weights in a binary glm and how to calculate them?
I have a dataset that includes four variables. Three of them are factors and one is constant. My response variable contains (0,1) so my glm is about logistic regression. My question is, how do I know …