Generalized Additive Models (GAM)
Uncover non-linear relationships in your data with GAM. Input your variables and smooth functions to get insights.
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Smooth Function Estimates
Predicted Values
Model Summary Statistics
What are Generalized Additive Models (GAM)?
Generalized Additive Models (GAMs) are flexible regression techniques that extend linear models by allowing for non-linear relationships between variables. Instead of assuming a straight-line relationship, GAMs model the dependent variable as a sum of smooth functions of the independent variables. This makes them powerful for uncovering complex patterns in data where linear assumptions fail. They are widely used in various fields like environmental science, epidemiology, and finance to understand and predict outcomes based on multiple factors.