Generalized Additive Models (GAM)

Generalized Additive Models (GAM) are a type of statistical model used to understand complex relationships between variables. They combine the flexibility of non-linear modeling with the interpretability of simpler models. In GAM, the effect of each predictor variable is modeled separately and added together to predict an outcome. This allows for capturing intricate patterns in data while still being able to see how each variable contributes. Gam are useful in fields like finance, biology, and social sciences where relationships are not always straightforward and help reveal trends and insights without assuming a specific overall shape.