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library(forecast) 
library(uroot)

data <- read.csv("armas16.csv") 
data <- na.omit(data) 

# VARIABLES 
nombres <- names(data)
nombres <-  nombres[2:length(nombres)]

for (nombre in nombres) {
  yt <- ts(data[,nombre], start = 1960, frequency = 4)
  print(nombre)
  modelo <- auto.arima(x = yt, 
                       seasonal = T, 
                       stepwise = F,
                       ic = "aicc")
  modelo
  summary(modelo)
  pred <- forecast(modelo,4)
  pred$mean
  
  fn <- paste(nombre,"_tsdisplay", ".jpg", sep = "")
  jpeg(filename = fn)
  par(bty = 'n')
  tsdisplay(yt, ylab = nombre)
  dev.off()
  
  fn <- paste(nombre,"_resid_tsdisplay", ".jpg", sep = "")
  jpeg(filename = fn)
  par(bty = 'n')
  tsdisplay(pred$residuals, ylab = nombre)
  dev.off()
  
  fn <- paste(nombre,"_forecast", ".jpg", sep = "")
  jpeg(filename = fn)
  par(bty = 'n')
  plot(pred, ylab = nombre)
  dev.off()
  
  # GUARDAR DATOS
  res <- c(nombre, pred$method, pred$mean)
  write(x = res, file = "res.txt", append = T, sep = "\t", ncolumns = 6)
}