Content deleted Content added
No edit summary |
|||
Line 3:
==Description==
Given a [[data]] set <math>\{y_i,\, x_{i1}, \ldots, x_{ip}\}_{i=1}^n</math> of ''n'' [[statistical unit]]s, where <math>\{x_{i1}, \ldots, x_{ip}\}_{i=1}^n</math> represent predictors and <math>y_i</math> is the outcome, the ''additive model'' takes the form
: <math>E[y_i|x_{i1}, \ldots, x_{ip}] = \beta_0+\sum_{j=1}^p f_j(x_{ij}) </math>
or
: <math>Y= \beta_0+\sum_{j=1}^p f_j(X_{j})+\varepsilon </math>
| |||