genlass_nonlinear.R

library(dplyr)
library(genlasso)

d <- data.frame(x = sample(-seq(-20,20,2), 1e5, replace = TRUE)) %>%
  mutate(event_rate = abs(round((x)/2)/10),
         y = rbinom(n(), 1, event_rate),
         x_fctr = as.factor(x))


y <- d$y
X <- model.matrix(y ~ x_fctr - 1, d)

edges <- c(1, 2)
for (i in 2:20) {
    edges <- c(edges, i, i+1)
}
gr <- graph(edges = edges, directed = FALSE)

fl <- fusedlasso(y, X, graph = gr, verbose = TRUE)
plot(fl, numbers = TRUE, vlines = FALSE)

library(reshape)
melt_beta = melt(fl$beta)
colnames(melt_beta) = c('beta_index',  'lambda', 'beta_coefficient')
library(ggplot2)
ggplot(melt_beta, aes(x = beta_index, y = beta_coefficient, group = as.factor(lambda), colour = as.factor(lambda))) + geom_line()