Generalized Linear Model
Generalized Linear Models (GLMs) are a powerful tool used in statistics to explain relationships between a dependent variable and one or more independent variables, while taking into account the influence of other factors. GLMs are especially useful when the dependent variable is not normally distributed, because they allow us to use different link functions to fit the relationship between the dependent variable and the independent variable(s). GLMs have become increasingly popular for modelling complex data sets, and for analyzing data with many potential confounding factors. GLMs are especially useful for predicting the probability of an event, such as a customer making a purchase decision, or detecting a trend in data over time. In addition, GLMs can help to identify key drivers of a given outcome, and can be used to examine interactions between variables.
← Journal of Model Based Research