# Two seasonal periods in ARIMA using R

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))
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?

-
Yes, you could use some Fourier terms as regressors and deal with the seasonality that way. –  Rob Hyndman Jan 15 '13 at 22:53

There are no R packages that handle multiple seasonality for ARIMA models as far as I know. You could try the forecast package which implements multiple seasonality using models based on exponential smoothing. The dshw, bats and tbats functions will all handle data with two seasonal periods.