Generalized Linear Model

A generalized linear model (GLM) is a statistical framework that relates a response variable to one or more predictors when the response may not follow a normal distribution. GLMs combine a linear predictor, formed from weighted coefficients and input variables, with a probability distribution and a link function that connects the predictor to the response mean. This structure supports continuous, binary, count, and proportion data while estimating predictor effects. In engineering, GLMs aid reliability analysis, defect detection, sensor calibration, and process monitoring, helping quantify risk, compare designs, and guide data-driven control and decision systems.

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