R Notebook

library(readr)
base_1<-read.csv("/Users/carloscarrillolazaro/Desktop/BASE_1.csv")
base_1<-base_1[,-1]
base<-matrix(rep(0,nrow(base_1)*2),ncol=2)
colnames(base)<-colnames(base_1)
for (i in seq(1, nrow(base_1), by = 3)) {
  base[i, 1] = sum(base_1[i:(i + 2), 1]) / 3
  base[i, 2] = sum(base_1[i:(i + 2), 2]) / 3
}
base[base==0]<-NA
base <- na.omit(base)
write.csv(base, file = "base.csv", )

base_2<-read.csv("/Users/carloscarrillolazaro/Desktop/Balanza_com.csv")
base_2<-base_2[,-1]
balanza_com<-matrix(rep(0,nrow(base_2)*2),ncol=2)
colnames(balanza_com)<-colnames(base_2)
for (i in seq(1, nrow(base_2), by = 3)) {
  balanza_com[i, 1] = sum(base_2[i:(i + 2), 1]) / 3
  balanza_com[i, 2] = sum(base_2[i:(i + 2), 2]) / 3
}
balanza_com[balanza_com==0]<-NA
balanza_com <- na.omit(balanza_com)
write.csv(balanza_com, file = "balanza_com.csv")

library(forecast)

data<-read.csv("/Users/carloscarrillolazaro/Desktop/base.csv")
variable_dep<-as.matrix(data$PIB)
variables_ind<-as.matrix(data[,c("EXP")])
ARIMA <- arima(variable_dep, order=c(4,2, 1), xreg=variables_ind)
newxreg <- variables_ind
pronostico <- predict(ARIMA, n.ahead = 4, newxreg = newxreg)

Warning in z[[1L]] + xm :
  longer object length is not a multiple of shorter object length

library(stats)

datos_historicos<-data$PIB
serie_temporal <- ts(datos_historicos, frequency = 4)  

modelo <- HoltWinters(serie_temporal)

pronostico <- forecast(modelo, h = 4)  

plot(pronostico)

datos_historicos<-data$EXP

serie_temporal <- ts(datos_historicos, frequency = 4) 

modelo <- HoltWinters(serie_temporal)

pronostico <- forecast(modelo, h = 4) 

plot(pronostico)