library(GAMBoost); library(parallel)
fit.gb <- list()

# Boosting
fit.gb <- mclapply(X = 1:100, mc.preschedule = FALSE, mc.cores = detectCores() - 1, FUN = function(b) {
  print(b)
  
  set.seed(b)
  load(paste("simulation/b", b, ".RData", sep = ""))
  
  gb <- GAMBoost(y = y, x = NULL, x.linear = X, standardize.linear = FALSE, family = binomial(), penalty.linear = 100, criterion = "deviance", stepno = 500)
  gb$eta <- gb$hatmatrix <- gb$obsvar <- gb$scoremat <- NULL

  return(gb)
})

save(list = "fit.gb", file = "fit.gb.RData")