
  library(AER)
  library(MASS)
  data(Boston)


  # find the optimal polynomial order of the polylog model
  
  
  
  
  
  
  
  
  
  # extract the R^2 from the selected model and assign it to R2


  # find the optimal polynomial order of the polylog model
  for(i in 4:1){
  mod  <- lm(medv ~ poly(log(lstat), i, raw = T), data = Boston)
  pval <- coeftest(mod, vcov = vcovHC)[(i+1), 4]
  if(pval < 0.05){
    print(i)
    break
    }
  }
  
  # extract the R^2 from the selected model and assign it to R2
  R2 <- summary(mod)$r.squared


  ex() %>% check_for()
  ex() %>% check_object("R2") %>% check_equal()
  success_msg("Correct! Using the sequential testing approach we get an optimal order of r=2.")