Estimacion del Modelo

library(readxl)
library(forecast)
## Warning: package 'forecast' was built under R version 4.0.5
## Registered S3 method overwritten by 'quantmod':
##   method            from
##   as.zoo.data.frame zoo
serie.ivae<- read_excel("C:/Users/CHELO/Downloads/ivae_SVL.xlsx",col_types = c("skip", "numeric"),
 skip = 5)
serie.ivae.ts <- ts(data = serie.ivae,
 start = c(2009, 1),
 frequency = 12)
serie.ivae.ts %>%
 autoplot(main = "IVAE, El Salvador 2009-2021[marzo]",
 xlab = "Años/Meses",
 ylab = "Indice")

#Estimación del componente de Tendencia-Ciclo a través de medias moviles

ma2_12 <- ma(serie.ivae.ts, 12, centre = TRUE)
autoplot(serie.ivae.ts,main = "IVAE, El Salvador 2009-2021[marzo]",
 xlab = "Años/Meses",
 ylab = "Indice")+
 autolayer(ma2_12,series = "Tt")
## Warning: Removed 12 row(s) containing missing values (geom_path).

#Cálculo de los Factores Estacionales (Componente St)

library(magrittr)
## Warning: package 'magrittr' was built under R version 4.0.5
Yt <- serie.ivae.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(2009, 1), frequency = 12)
autoplot(St,
 main = "Factores Estacionales",
 xlab = "Años/Meses",
 ylab = "Factor Estacional")

# Cálculo del Componente Irregular It

It<-Yt-Tt-St
autoplot(It,
 main = "Componente Irregular",
 xlab = "Años/Meses",
 ylab = "It")

#Descomposición Aditiva (usando la libreria stats)

descomposicion_aditiva<-decompose(serie.ivae.ts,type = "additive")
autoplot(descomposicion_aditiva,main="Descomposición Aditiva",xlab="Años/Meses")

#Descomposición Aditiva usando libreria feasts

library(tsibble)
## Warning: package 'tsibble' was built under R version 4.0.5
## 
## Attaching package: 'tsibble'
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, union
library(feasts)
## Warning: package 'feasts' was built under R version 4.0.5
## Loading required package: fabletools
## Warning: package 'fabletools' was built under R version 4.0.5
## 
## Attaching package: 'fabletools'
## The following objects are masked from 'package:forecast':
## 
##     accuracy, forecast
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 4.0.5
Yt %>% as_tsibble() %>%
 model(
 classical_decomposition(value, type = "additive")
 ) %>%
 components() %>%
 autoplot() +
 labs(title = "Descomposición Clásica Aditiva, IVAE")+xlab("Años/Meses")
## Warning: Removed 6 row(s) containing missing values (geom_path).

#Componente Tendencia Ciclo [Tt=TCt]

Tt<- ma(serie.ivae.ts, 12, centre = TRUE)
autoplot(Tt,main = "Componente Tendencia [Ciclo]", xlab = "Años/Meses",ylab = "Tt")

#Cálculo de Factores Estacionales [St]

SI<-Yt/Tt #Serie sin tendencia.
St <- tapply(SI, cycle(SI), mean, na.rm = TRUE)
St <- St*12/sum(St)
#Generar la serie de factores para cada valor de la serie original
St <-
 rep(St, len = length(Yt)) %>% ts(start = c(2009, 1), frequency = 12)
autoplot(St,
 main = "Factores Estacionales",
 xlab = "Años/Meses",
 ylab = "Factor Estacional")

#Cálculo del Componente Irregular [It]

It<-Yt/(Tt*St)
autoplot(It,
 main = "Componente Irregular",
 xlab = "Años/Meses",
 ylab = "It")

#Descomposición Multiplicativa (usando la libreria stats):

descomposicion_multiplicatica<-decompose(serie.ivae.ts,type = "multiplicative")
autoplot(descomposicion_multiplicatica,main="Descomposición Multiplicativa",xlab="Años/Meses")

#Descomposición Multiplicativa usando libreria feasts

library(tsibble)
library(feasts)
library(ggplot2)
Yt %>% as_tsibble() %>%
 model(
 classical_decomposition(value, type = "multiplicative")
 ) %>%
 components() %>%
 autoplot() +
 labs(title = "Descomposición Clásica Multiplicativa, IVAE")+xlab("Años/Meses")
## Warning: Removed 6 row(s) containing missing values (geom_path).