I'm currently using R to predict a time series with these instructions:
X <- ts(datas, frequency=24) X.arima <- Arima(X, order=c(2,1,0), seasonal=c(1,1,1)) pred <- predict(X.arima, n.ahead=24) plot.ts(pred$pred)
As you can see I've data each hour, and I chose the seasonal period of 24 (one day).
I would like to improve my forecasting using an additional seasonal period in order to include the seasonal component of the week (seasonal length of 7*24=168 data)
Is there any method for this? How do you do it?
UPDATE: I've read this (your) blog page, maybe can I use the external regressors to simulate a second seasonal period?