Generalized linear models (GLMs) are a class of statistical models that extend traditional linear regression to accommodate various types of response variables, including binary, count, and continuous data. GLMs provide a flexible framework for modeling relationships between a dependent variable and one or more independent variables, utilizing link functions to relate the mean of the response variable to the predictors.
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