In GAMs, each predictor can be represented by a smooth function, typically splines. The model can be written as:
g(E(Y)) = β0 + f1(X1) + f2(X2) + ... + fn(Xn)
Here, g(E(Y)) is the link function, β0 is the intercept, and f1(X1), f2(X2), ... fn(Xn) are smooth functions of the predictors. These smooth functions can be fitted using methods like splines or kernel smoothing.
