##########################################
#USANDO TIME SERIES (SÉRIES TEMPORAIS)
#DADOS: MÁRIO
#############################################

#####INSTALANDO OS PACOTES######
install.packages("ggfortify")
library(ggfortify)
install.packages("fpp2")
library(fpp2)

####LENDO OS DADOS#####
mario <- read.csv("mario.csv", header=TRUE)
str(mario)

####TRANSFORMANDO MARIO EM UMA TIME SERIES CLASS (ts)########
mario_ts <- ts(mario[,2], start=c(2002), frequency=6)

#####DECOMPONDO O MÁRIO######
d<-decompose(mario_ts)
plot(d)
plot(d$x)
plot(d$trend)
plot(d$seasonal)
plot(d$random)
plot(d$figure)

####OUTRA MANEIRA DE PLOTAR####
autoplot(mario_ts, ts.colour = "blue")
autoplot(ma(mario_ts,5), ts.colour = "red", ts.size = 1)
autoplot(mario_ts, ts.colour = "blue", ts.size = 0.5) +  
  autolayer(ma(mario_ts,5), series="5-MA") + 
  theme(axis.line.x = element_line(size = 0.5, colour = "black"),
                                                   axis.line.y = element_line(size = 0.5, colour = "black"),
                                                   axis.line = element_line(size=1, colour = "black"),
                                                   panel.grid.major = element_blank(),
                                                   panel.grid.minor = element_blank(),
                                                   panel.border = element_blank(),
                                                   panel.background = element_blank(),
                                                   axis.text.x=element_text(size=6, face="bold", color = "black", angle = 45, hjust=1),
                                                   axis.text.y=element_text(size=12, face="bold"),
                                                   axis.title.y=element_text(size=14, face = "bold"),
                                                   axis.title.x = element_text (size = 16, face = "bold"), 
                                                   legend.title = element_blank(),
                                                   legend.text = element_text(size=11))

####PLOTANDO O MÁRIO POR ANO######  
ggseasonplot(mario_ts) + 
  theme(axis.line.x = element_line(size = 0.5, colour = "black"),
        axis.line.y = element_line(size = 0.5, colour = "black"),
        axis.line = element_line(size=1, colour = "black"),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        panel.border = element_blank(),
        panel.background = element_blank(),
        axis.text.x=element_text(size=12, face="bold", color = "black", angle = 0, hjust=1),
        axis.text.y=element_text(size=12, face="bold"),
        axis.title.y=element_text(size=14, face = "bold"),
        axis.title.x = element_text (size = 16, face = "bold"), 
        legend.title = element_blank(),
        legend.text = element_text(size=11))


#####PLOTANDO O MÁRIO POR PERÍODO####
ggsubseriesplot(mario_ts) + geom_line(color = "black") +
    theme(axis.line.x = element_line(size = 0.5, colour = "black"),
        axis.line.y = element_line(size = 0.5, colour = "black"),
        axis.line = element_line(size=1, colour = "black"),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        panel.border = element_blank(),
        panel.background = element_blank(),
        axis.text.x=element_text(size=12, face="bold", color = "black", angle = 0, hjust=1),
        axis.text.y=element_text(size=12, face="bold"),
        axis.title.y=element_text(size=14, face = "bold"),
        axis.title.x = element_text (size = 16, face = "bold"), 
        legend.title = element_blank(),
        legend.text = element_text(size=11))


############################
#MODELAGEM DE SÉRIES TEMPORAIS
################################

####MODELO SIMPLES NAIVE###############
mario_naive<-naive(mario_ts)
summary(mario_naive)
print(mario_naive)
plot(mario_naive$x)
plot(mario_naive$fitted)

fitted_layer <- forecast::autolayer(mario_naive$fitted, series="Fitted")
fitted_values <- fitted_layer$layer_data()
autoplot(mario_naive) + fitted_layer + geom_point(data = fitted_values, aes(x=timeVal, y=seriesVal), color="red")

plot(forecast(mario_naive))



#####MODELO MAIS ROBUSTO HW#####
hw_mario<-hw(mario_ts)
print(hw_mario)
summary(hw_mario)
checkresiduals(hw_mario)
plot(hw_mario$x)
plot(hw_mario$fitted)
autoplot(forecast(hw_mario)) + autolayer(hw_mario$fitted, size =1)

#####MODELO ROBUSTO MAIS USADO ARIMA####
arima_mario<-auto.arima(mario_ts)
print(hw_mario)
summary(arima_mario)
checkresiduals(arima_mario)
plot(arima_mario$x)
plot(arima_mario$fitted)
autoplot(forecast(arima_mario)) + autolayer(arima_mario$fitted, size = 1)

####MODELO ROBUSTO STLF#####
mario_stlm<-stlf(mario_ts)
print(mario_stlm)
summary(mario_stlm)
checkresiduals(mario_stlm)
plot(mario_stlm$x)
plot(mario_stlm$fitted)
autoplot(mario_stlm$x, ts.colour = "blue", ts.size = 0.5) +  
  autolayer(mario_stlm$fitted, series="fitted", size =1) + 
  theme(axis.line.x = element_line(size = 0.5, colour = "black"),
        axis.line.y = element_line(size = 0.5, colour = "black"),
        axis.line = element_line(size=1, colour = "black"),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        panel.border = element_blank(),
        panel.background = element_blank(),
        axis.text.x=element_text(size=6, face="bold", color = "black", angle = 45, hjust=1),
        axis.text.y=element_text(size=12, face="bold"),
        axis.title.y=element_text(size=14, face = "bold"),
        axis.title.x = element_text (size = 16, face = "bold"), 
        legend.title = element_blank(),
        legend.text = element_text(size=11))

plot(forecast(mario_stlm))


####DECOMPONDO USANDO STL####################
decomp <- stl(mario_ts, s.window = "periodic")
plot(decomp)
plot(forecast(decomp))