What is GLM?

GLM typically refers to Generalized Linear Models. These are a flexible generalization of ordinary least squares regression that allows for response variables that have error distribution models other than a normal distribution. GLMs are used for regression analysis when the response variable is not normally distributed, such as binary data (logistic regression), count data (Poisson regression), or skewed data (gamma regression). They consist of a random component (probability distribution of the response variable), a systematic component (linear predictor), and a link function that relates the linear predictor to the expected value of the response.