Editing Generalized linear model (section)

=== Generalized additive models ===
[[Generalized additive model]]s (GAMs) are another extension to GLMs in which the linear predictor ''η'' is not restricted to be linear in the covariates '''X''' but is the sum of [[smoothing|smoothing functions]] applied to the ''x<sub>i</sub>''s:
: <math>\eta = \beta_0 + f_1(x_1) + f_2(x_2) + \cdots \,\!</math>

The smoothing functions ''f<sub>i</sub>'' are estimated from the data. In general this requires a large number of data points and is computationally intensive.{{sfn|Hastie|Tibshirani|1990}}{{sfn|Wood|2006}}