## Warning in model.matrix.default(mt, mf, contrasts): non-list contrasts argument
## ignored
##
## Call: gam(formula = wage ~ s(year, 4) + s(age, 5) + education, data = Wage)
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -119.43 -19.70 -3.33 14.17 213.48
##
## (Dispersion Parameter for gaussian family taken to be 1236)
##
## Null Deviance: 5222086 on 2999 degrees of freedom
## Residual Deviance: 3689770 on 2986 degrees of freedom
## AIC: 29888
##
## Number of Local Scoring Iterations: 2
##
## Anova for Parametric Effects
## Df Sum Sq Mean Sq F value Pr(>F)
## s(year, 4) 1 27162 27162 22 2.9e-06 ***
## s(age, 5) 1 195338 195338 158 < 2e-16 ***
## education 4 1069726 267432 216 < 2e-16 ***
## Residuals 2986 3689770 1236
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Anova for Nonparametric Effects
## Npar Df Npar F Pr(F)
## (Intercept)
## s(year, 4) 3 1.1 0.35
## s(age, 5) 4 32.4 <2e-16 ***
## education
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
plot(gam1, se=TRUE, col="blue")
gam.lr <- gam(I(wage > 250) ~ year + s(age, df=5) + education, family = binomial, data = Wage)
## Warning in model.matrix.default(mt, mf, contrasts): non-list contrasts argument
## ignored
plot(gam.lr, se = T, col="red")
