gams with glmnet

gistfile1.txt

library(dplyr)
library(glmnet)
library(splines)
library(tidyr)
library(ggplot2)
library(magrittr)

d <- data_frame(cov1 = rnorm(100),
                cov2 = rnorm(100),
                y = cov1 ^ 2 + rnorm(100, sd = 0.3))

spline <- bs(d$cov1)

d <- cbind(d, spline)


ggplot(d %>% gather('var', 'value', -y), aes(value, y)) + 
  geom_point() + 
  geom_smooth() +
  facet_wrap(~ var, scale = 'free_x')



model.lm <- lm(y ~ `1` + `2` + `3`, data = d)

gampreds <- data_frame(x = seq(-4, 4, length.out = 1000),
                       y = predict(model.lm, newdata = predict(spline, seq(-4, 4, length.out = 1000))))



ggplot(gampreds, aes(x, y)) + 
  geom_line() +
  geom_point(data = d, aes(cov1, y))


model <- glmnet(x = as.matrix(d %>% select(-y, -cov1)), y = d$y)

coef(model, s = 0.01)


        
        
elasticnetpreds <- cbind(cov1 = seq(-4, 4, length.out = 1000),
                              predict(model, 
                                      newx = cbind(cov2 = 0, predict(spline, seq(-4, 4, length.out = 1000))),
                                      s = c(0.01, 0.1)) %>% set_colnames(c('pred_w_lambda1', 'pred_w_lambda2'))
                    ) %>% data.frame



ggplot(gampreds, aes(x, y)) + 
  geom_line(colour = 'red') +
  geom_point(data = d, aes(cov1, y)) +
  geom_line(data = elasticnetpreds, aes(cov1, pred_w_lambda2), colour = 'steelblue') +
  geom_line(data = elasticnetpreds, aes(cov1, pred_w_lambda1), colour = 'darkblue')