Series de Tiempo

library(foreign)
baseP<-read.csv("C:/ST FINAL/BaseSTCM.csv")
attach(baseP)

library(TSA)

## Loading required package: leaps

## Loading required package: locfit

## locfit 1.5-9.1    2013-03-22

## Loading required package: mgcv

## Loading required package: nlme

## This is mgcv 1.8-23. For overview type 'help("mgcv-package")'.

## Loading required package: tseries

## 
## Attaching package: 'TSA'

## The following objects are masked from 'package:stats':
## 
##     acf, arima

## The following object is masked from 'package:utils':
## 
##     tar

STCM<-ts(baseP$pasajeros,start = c(1986,1),frequency = 12)

library(ggplot2)
library(forecast)

## 
## Attaching package: 'forecast'

## The following object is masked from 'package:nlme':
## 
##     getResponse

2. Graficar los datos, analizar patrones y observaciones atípicas. Apoye su análisis con una descomposición clásica.

autoplot(STCM)+ylab("Número de Pasajeros Promedio")+xlab("Años")+ggtitle("Pasajeros del STCM 1986-2018")