Descomposición de Series Temporales
library(readxl)
library(forecast)
serie.imae<- read_excel("C:/Users/LENOVO/Downloads/IMAE_SLV.xlsx",
col_types = c("skip", "numeric"),
skip = 5)
serie.imae.ts<- ts(data = serie.imae,
start = c(2018, 1),
frequency = 12)
serie.imae.ts
## Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
## 2018 105.1 102.5 108.4 108.0 112.5 113.6 108.7 111.9 107.5 105.9 112.2 120.0
## 2019 107.9 106.1 112.7 109.8 114.8 114.7 111.1 113.2 111.8 108.7 116.7 122.6
## 2020 109.2 109.7 103.9 87.3 89.6 96.0 97.8 103.5 107.9 106.0 111.7 120.8
## 2021 107.6 108.0 113.3 110.6 115.5 117.2 112.1 115.3 114.7 111.8 118.0 126.3
## 2022 111.4 111.8 119.1 112.5 121.0 119.3 114.6 120.3 118.3 115.7 121.6 127.6
## 2023 113.1 111.2 120.5
Modelo Aditivo
Componente de Tendencia Tt (Componente TCt)
ma2_12<- ma(serie.imae.ts, 12, centre = TRUE)
autoplot(serie.imae.ts,main = "EL Salvador 2009-2021 (Marzo)",
xlab = "Años/Meses",
ylab = "Indice")+
autolayer(ma2_12,series = "Tt")
Cálculo de los Factores Estacionales [Componente St]
library(magrittr)
Yt <- serie.imae.ts
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(2018, 1), frequency = 12)
autoplot(St,
main = "Estacionales",
xlab = "Años/Meses",
ylab = "Factor Estacional")
Cálculo del Componente Irregular It
It <- Yt - Tt - St
autoplot(It,
main = "Irregular",
xlab = "Años/Meses",
ylab = "It")
Descomposición Aditiva (usando libreria stats)
library(stats)
descomposición_aditi <- decompose(serie.imae.ts, type = "additive")
autoplot (descomposición_aditi, main= "Descomposición Aditiva", xlab = "Años/Meses")
Descomposición Aditiva (usando feasts)
library(tsibble)
library(feasts)
library(ggplot2)
Yt %>% as_tsibble() %>%
model(
classical_decomposition(value, type ="additive")
) %>%
components () %>%
autoplot() +
labs(title = "Descomposición Clásica Aditiva")+xlab("Años/Meses")
Modelo Multiplicativo
Componente Tendencia Ciclo (Tt=TCt)
Tt<- ma(serie.imae.ts, 12, centre = TRUE)
autoplot(Tt, main = "Componente Tendencia", xlab = "Años/Meses", ylab = "Tt")
Cálculo de Factores Estacionales (St)
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(2018, 1), frequency = 12)
autoplot(St,
main = "Factores Estacionales",
xlab = "Años/Meses",
ylab = "Factor Estacional")
Componente Irregular [It]
It <- Yt/(Tt*St)
autoplot(It,
main = "Componente Irregular",
xlab = "Años/Meses",
ylab = "It")
Descomposición Multiplicativa (usando libreria stats)
library(stats)
descomposición_multiplicativa <- decompose(serie.imae.ts, type = "multiplicative")
autoplot(descomposición_multiplicativa, main ="Descomposición Multiplicativa", xlab="Años/Meses")
Descomposición Multiplicativa (usando libreria TSstudio)
library(TSstudio)
ts_decompose(Yt, type = "multiplicative", showline = TRUE)
ts_seasonal(Yt, type = "box", title = " Valores Estacionales")