library(readxl)
library(mFilter)
library(forecast)
library(dplyr)

# Carga de los datos
PIB_trimestral <- read_excel("D:/Usuario/Descargas/datos_PIB_trim_CA.xlsx",skip = 6)
colnames(PIB_trimestral) <- c("Fechas", "Costa Rica", "El Salvador", "Guatemala", "Honduras", "Nicaragua", "República Dominicana", "Panamá")

# Personalizada
PIB_trimestral$`Costa Rica` <- as.numeric(PIB_trimestral$`Costa Rica`)
costa_rica <- ts(PIB_trimestral$`Costa Rica`, start = c(1991, 1), frequency = 4)
costa_rica <- costa_rica[is.finite(costa_rica)]
hp_result_costa_rica <- hpfilter(costa_rica, freq = 1600)
trend <- hp_result_costa_rica$trend
cycle <- hp_result_costa_rica$cycle
plot(costa_rica, type = "l", main = "Filtro de Hodrick-Prescott - Costa Rica", ylab = "PIB", xlab = "Tiempo")
lines(trend, col = "blue", lwd = 2)
legend("topleft", legend = c("Costa Rica", "Tendencia (Filtro HP)"), col = c("black", "blue"), lty = 1, lwd = 2)

plot(cycle, type = "l", main = "Componente Ciclico", ylab = "Ciclo", xlab = "Tiempo")

# Rápida
plot(hp_result_costa_rica, ask = FALSE)

# Personalizada
PIB_trimestral$`El Salvador` <- as.numeric(PIB_trimestral$`El Salvador`)
el_salvador <- ts(PIB_trimestral$`El Salvador`, start = c(1990, 1), frequency = 4)
el_salvador <- el_salvador[is.finite(el_salvador)]
hp_result_el_salvador <- hpfilter(el_salvador, freq = 1600)
trend <- hp_result_el_salvador$trend
cycle <- hp_result_el_salvador$cycle
plot(el_salvador, type = "l", main = "Filtro de Hodrick-Prescott - El Salvador", ylab = "PIB", xlab = "Tiempo")
lines(trend, col = "red", lwd = 2)
legend("topleft", legend = c("El Salvador", "Tendencia (Filtro HP)"), col = c("black", "red"), lty = 1, lwd = 2)

plot(cycle, type = "l", main = "Componente Ciclico", ylab = "Ciclo", xlab = "Tiempo")

# Rápida
plot(hp_result_el_salvador, ask = FALSE)

# Personalizada
PIB_trimestral$Guatemala <- as.numeric(PIB_trimestral$Guatemala)
guatemala <- ts(PIB_trimestral$Guatemala, start = c(2001, 1), frequency = 4)
guatemala <- guatemala[is.finite(guatemala)]
hp_result_guatemala <- hpfilter(guatemala, freq = 1600)
trend <- hp_result_guatemala$trend
cycle <- hp_result_guatemala$cycle
plot(guatemala, type = "l", main = "Filtro de Hodrick-Prescott - Guatemala", ylab = "PIB", xlab = "Tiempo")
lines(trend, col = "green", lwd = 2)
legend("topleft", legend = c("Guatemala", "Tendencia (Filtro HP)"), col = c("black", "green"), lty = 1, lwd = 2)

plot(cycle, type = "l", main = "Componente Ciclico", ylab = "Ciclo", xlab = "Tiempo")

# Rápida
plot(hp_result_guatemala, ask = FALSE)

# Personalizada
PIB_trimestral$Honduras <- as.numeric(PIB_trimestral$Honduras)
honduras <- ts(PIB_trimestral$Honduras, start = c(2000, 1), frequency = 4)
honduras <- honduras[is.finite(honduras)]
hp_result_honduras <- hpfilter(honduras, freq = 1600)
trend <- hp_result_honduras$trend
cycle <- hp_result_honduras$cycle
plot(honduras, type = "l", main = "Filtro de Hodrick-Prescott - Honduras", ylab = "PIB", xlab = "Tiempo")
lines(trend, col = "purple", lwd = 2)
legend("topleft", legend = c("Honduras", "Tendencia (Filtro HP)"), col = c("black", "purple"), lty = 1, lwd = 2)

plot(cycle, type = "l", main = "Componente Ciclico", ylab = "Ciclo", xlab = "Tiempo")

# Rápida
plot(hp_result_honduras, ask = FALSE)

# Personalizada
PIB_trimestral$Nicaragua <- as.numeric(PIB_trimestral$Nicaragua)
nicaragua <- ts(PIB_trimestral$Nicaragua, start = c(2006, 1), frequency = 4)
nicaragua <- nicaragua[is.finite(nicaragua)]
hp_result_nicaragua <- hpfilter(nicaragua, freq = 1600)
trend <- hp_result_nicaragua$trend
cycle <- hp_result_nicaragua$cycle
plot(nicaragua, type = "l", main = "Filtro de Hodrick-Prescott - Nicaragua", ylab = "PIB", xlab = "Tiempo")
lines(trend, col = "orange", lwd = 2)
legend("topleft", legend = c("Nicaragua", "Tendencia (Filtro HP)"), col = c("black", "orange"), lty = 1, lwd = 2)

plot(cycle, type = "l", main = "Componente Ciclico", ylab = "Ciclo", xlab = "Tiempo")

# Rápida
plot(hp_result_nicaragua, ask = FALSE)

# Personalizada
PIB_trimestral$`República Dominicana` <- as.numeric(PIB_trimestral$`República Dominicana`)
republica_dominicana <- ts(PIB_trimestral$`República Dominicana`, start = c(1991, 1), frequency = 4)
republica_dominicana <- republica_dominicana[is.finite(republica_dominicana)]
hp_result_republica_dominicana <- hpfilter(republica_dominicana, freq = 1600)
trend <- hp_result_republica_dominicana$trend
cycle <- hp_result_republica_dominicana$cycle
plot(republica_dominicana, type = "l", main = "Filtro de Hodrick-Prescott - República Dominicana", ylab = "PIB", xlab = "Tiempo")
lines(trend, col = "pink", lwd = 2)
legend("topleft", legend = c("República Dominicana", "Tendencia (Filtro HP)"), col = c("black", "pink"), lty = 1, lwd = 2)

plot(cycle, type = "l", main = "Componente Ciclico", ylab = "Ciclo", xlab = "Tiempo")

# Rápida
plot(hp_result_republica_dominicana, ask = FALSE)

# Personalizada
PIB_trimestral$Panamá <- as.numeric(PIB_trimestral$Panamá)
Panamá <- ts(PIB_trimestral$Panamá, start = c(1996, 1), frequency = 4)
Panamá <- Panamá[is.finite(Panamá)]
hp_result_Panama <- hpfilter(Panamá, freq = 1600)
trend <- hp_result_Panama$trend
cycle <- hp_result_Panama$cycle
plot(Panamá, type = "l", main = "Filtro de Hodrick-Prescott - Panamá", ylab = "PIB", xlab = "Tiempo")
lines(trend, col = "yellow", lwd = 2)
legend("topleft", legend = c("Panamá", "Tendencia (Filtro HP)"), col = c("black", "yellow"), lty = 1, lwd = 2)

plot(cycle, type = "l", main = "Componente Ciclico", ylab = "Ciclo", xlab = "Tiempo")

# Rápida
plot(hp_result_Panama, ask = FALSE)