gistfile1.txt

Eggsdf<-as.data.frame(Eggs)
far1 <- function(x, h){forecast(Arima(x, order=c(1,0,0), seasonal=FALSE), h=h)}
e <- tsCV(Eggsdf$egg_count, far1, h=1)
fc <- c(NA, Eggsdf$egg_count[2:149] - e[1:148])

train <-window(Eggs, end=2021.310)
autoplot(train)+theme_bw()
test  <-window(Eggs, start=2021.311)

m1 <- auto.arima(train, 
                 ic="aic", 
                 seasonal=FALSE, 
                 stationary=TRUE, 
                 stepwise=FALSE, 
                 approximation=FALSE)
plot(m1)
summary(m1)
plot(forecast(m1, h=43))
ggtsdiag(m1, gof.lag = 14)+theme_bw()