I have a data set of daily values that I would like to fit an ARIMA model. I also have an additional data set of weekly values that I believe would serve well as an external regressor in the ARIMA model. From my understanding, the regressor must have the same length as the primary time series. I am wondering how to handle a situation like this. Would it make more sense to aggregate the daily data to weekly, somehow expand the weekly data to the daily level (e.g. repeat values), or perhaps a different approach entirely? For what it may be worth, I am generally using
R and the
If we extend the question a little further, let's say there are two external regressors, one at the daily level and another at the weekly. Would the approach differ here as well?