Descompocición de series temporales
Descomposición de Series Temporales (Enfoque Tradicional)
library(readxl)
library(forecast)
library(dplyr)
Ivae <- read_excel("C:/Users/DELL/Desktop/Programacion-en-R/Econometria/Tareas_Tercer_Parcial/IVAE.xlsx", col_types = c("skip", "numeric"), skip = 5)
Serie.Ivae <- ts(data = Ivae, start = c(2009,1), frequency = 12)
Serie.Ivae %>% autoplot(main = "IVAE de El Salvador 2009-2021[Marzo]",
xlab = "años",
ylab = "Indice")
1. Modelo Aditivo
1.1. Componente Tendencia Ciclo TCt
ma2_12 <- ma(Serie.Ivae, 12, centre = TRUE)
autoplot(Serie.Ivae, main = "IVAE de El Salvador", xlab = "Años", ylab = "Indice") +
autolayer(ma2_12, series = "Tt")
1.2. Factores Estacionales | Componente St
library(magrittr)
Yt <- Serie.Ivae
Tt <- ma2_12
SI <- Yt - Tt
St <- tapply(SI, cycle(SI), mean, na.rm = TRUE)
St <- St - sum(St) / 12
St <- rep(St, len = length(Yt)) %>% ts(start = c(2009, 1), frequency = 12)
autoplot(St, main = "Factores Estacinales",
xlab = "Años",
ylab = "Factor Estacional")
1.3. Componente Irregular
2. Modelo Multiplicativo
2.1. Componente Tendencia Ciclo (Tt = TCt)
Tt <- ma(Serie.Ivae, 12, centre = TRUE)
autoplot(Tt, main = "Componente Tendencial (Ciclo)", xlab = "Años", ylab = "Tt")
2.2. Factores Estacionales
SI <- Yt/Tt
St <- tapply(SI, cycle(SI), mean, na.rm = TRUE)
St <- St*12/sum(St)
St <- rep(St, len = length(Yt)) %>% ts(start = c(2009, 1), frequency = 12)
autoplot(St, main = "Factores Estacionales",
xlab = "Años", ylab = "St")