library(readxl)
library(tidyr)
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(forecast)
## Registered S3 method overwritten by 'quantmod':
##   method            from
##   as.zoo.data.frame zoo
IVAE_03_22 <- read_excel("C:/Users/lupita nieto/Downloads/IVAE_03_22.xlsx", 
    skip = 6, n_max = 10)
## New names:
## ā€¢ `86.73` -> `86.73...2`
## ā€¢ `86.73` -> `86.73...27`
## ā€¢ `100.64` -> `100.64...72`
## ā€¢ `100.64` -> `100.64...82`
## ā€¢ `110.71` -> `110.71...91`
## ā€¢ `110.71` -> `110.71...144`
data.ivae<-pivot_longer (data =  IVAE_03_22[1,],names_to = "vars",cols = 2:160,values_to = "indice") %>% select("indice")
data.ivae.ts<- data.ivae %>% ts(start = c(2009,1),frequency = 12)
data.ivae.ts %>% 
  autoplot(main ="IVAE ENE 2009- MAR 2022",
           xlab="AƱos/Meses",
           ylab="Indice")

Descomposicion Aditiva

library(forecast)
#DescomposiciĆ³n aditiva IVAE
descompocicion_aditiva<-decompose(data.ivae.ts,type = "additive")
#grĆ”fico de la descompociciĆ³n
autoplot(descompocicion_aditiva, main="DescomposiciĆ³n de la serie aditiva")

#grƔfico de la serie original y el componente tendencia ciclo
Yt<-descompocicion_aditiva$x
TC<-descompocicion_aditiva$trend
autoplot(Yt,
         main = "DescomposiciĆ³n IVAE ENE 2009 - MAR 2022")+
  autolayer(TC)
## Warning: Removed 12 row(s) containing missing values (geom_path).

library(tidyr)
library(dplyr)
library(forecast)
data.ivae_agricultura<-pivot_longer(data = IVAE_03_22[2,],names_to = "vars",cols = 2:160,values_to = "indice") %>% select("indice")
data.ivae.ts_agricultura<- data.ivae_agricultura %>% ts(start = c(2009,1),frequency = 12)
data.ivae.ts_agricultura %>% 
  autoplot(main ="Agricultura, GanaderĆ­a, Silvicultura y Pesca ENE 2009 - MAR 2022",
           xlab="AƱos/Meses",
           ylab="Indice")

library(forecast)
#DescomposiciĆ³n aditiva
descompocicion_aditiva_agricultura<-decompose(data.ivae.ts,type = "additive")
#grĆ”fico de la descompociciĆ³n
autoplot(descompocicion_aditiva_agricultura, main="Agricultura, GanaderĆ­a, Silvicultura y Pesca ENE 2009 - MAR 2022")

#grƔfico de la serie original y el componente tendencia ciclo
Yt_agricultura<-descompocicion_aditiva_agricultura$x
TC_agricultura<-descompocicion_aditiva_agricultura$trend
autoplot(Yt_agricultura,
         main = "Agricultura, GanaderĆ­a, Silvicultura y Pesca ENE 2009 - MAR 2022")+
  autolayer(TC_agricultura)
## Warning: Removed 12 row(s) containing missing values (geom_path).

Indice De Produccion Industrial

library(tidyr)
library(dplyr)
library(forecast)

data.ivae_IPI<-pivot_longer(data = IVAE_03_22[3,],names_to = "vars",cols = 2:160,values_to = "indice") %>% select("indice")
data.ivae.ts_IPI<- data.ivae_IPI %>% ts(start = c(2009,1),frequency = 12)
data.ivae.ts_IPI %>% 
  autoplot(main ="Indice de Produccion Industrial ENE 2009 - MAR 2022",
           xlab="AƱos/Meses",
           ylab="Indice")

library(forecast)
#DescomposiciĆ³n aditiva
descompocicion_aditiva_IPI<-decompose(data.ivae.ts_IPI,type = "additive")
#grĆ”fico de la descompociciĆ³n
autoplot(descompocicion_aditiva_IPI, main="Indice de Produccion Industrial")

#grƔfico de la serie original y el componente tendencia ciclo
Yt_IPI<-descompocicion_aditiva_IPI$x
TC_IPI<-descompocicion_aditiva_IPI$trend
autoplot(Yt_IPI,
         main = "Indice de Produccion Industrial 2009- MAR 2022")+
  autolayer(TC_IPI)
## Warning: Removed 12 row(s) containing missing values (geom_path).

Descomposicion De Series Temporales

library(readxl)
library(tidyr)
library(dplyr)
library(forecast)
data.ivae_seriet<-pivot_longer(data = IVAE_03_22[4,],names_to = "vars",cols = 2:160,values_to = "indice") %>% select("indice")
data.ivae.ts_seriet<- data.ivae %>% ts(start = c(2009,1),frequency = 12)
data.ivae.ts_seriet %>% 
  autoplot(main ="ConstrucciĆ³n ENE 2009- MAR 2022",
           xlab="AƱos/Meses",
           ylab="Indice")

library(forecast)
#DescomposiciĆ³n aditiva
descompocicion_aditiva_seriet<-decompose(data.ivae.ts_seriet,type = "additive")
#grĆ”fico de la descompociciĆ³n
autoplot(descompocicion_aditiva_seriet, main="Indice de producciĆ³n Industrial (IPI) ENE 2009- MAR 2022")

#grƔfico de la serie original y el componente tendencia ciclo
Yt_seriet<-descompocicion_aditiva_seriet$x
TC_seriet<-descompocicion_aditiva_seriet$trend
autoplot(Yt_seriet,
         main = "Indice de producciĆ³n Industrial (IPI) ENE 2009- MAR 2022")+
  autolayer(TC_seriet)
## Warning: Removed 12 row(s) containing missing values (geom_path).

Comercio, Actividades, Transporte y Almacenamiento

library(readxl)
library(tidyr)
library(dplyr)
library(forecast)
data.ivae_cata<-pivot_longer(data = IVAE_03_22[5,],names_to = "vars",cols = 2:160,values_to = "indice") %>% select("indice")
data.ivae.ts_cata<- data.ivae %>% ts(start = c(2009,1),frequency = 12)
data.ivae.ts_cata %>% 
  autoplot(main ="Comercio, Actividades, Transporte y Almacenamiento  ENE 2009- MAR 2022",
           xlab="AƱos/Meses",
           ylab="Indice")

library(forecast)
#DescomposiciĆ³n aditiva
descompocicion_aditiva_cata<-decompose(data.ivae.ts_cata,type = "additive")
#grĆ”fico de la descompociciĆ³n
autoplot(descompocicion_aditiva_cata, main="Indice de Produccion Industrial")

#grƔfico de la serie original y el componente tendencia ciclo
Yt_cata<-descompocicion_aditiva_cata$x
TC_cata<-descompocicion_aditiva_cata$trend
autoplot(Yt_cata,
         main = "Comercio, Actividades, Transporte y Almacenamiento  ENE 2009- MAR 2022")+
  autolayer(TC_cata)
## Warning: Removed 12 row(s) containing missing values (geom_path).

library(readxl)
library(tidyr)
library(dplyr)
library(forecast)
data.ivae__ic<-pivot_longer(data = IVAE_03_22[6,],names_to = "vars",cols = 2:160,values_to = "indice") %>% select("indice")
data.ivae.ts_ic<- data.ivae %>% ts(start = c(2009,1),frequency = 12)
data.ivae.ts_ic %>% 
  autoplot(main ="Comercio, Actividades, Transporte y Almacenamiento  ENE 2009- MAR 2022",
           xlab="AƱos/Meses",
           ylab="Indice")