Hello JMP-Com,
I got this question from a customer who wanted to use either ARIMA models or time series forecasting (TSF) for their application.
Column 1 is a time stamp
Column 2- Column N has the data points
The Question: Can the ARIMA platform or TSF account for contributions from lag points that are in a different time scale?
For example; say I have monthly sales data and I know the sales in April are impactful to the sales in June. So I know that a lag of 2 months is important for my model. But is there a weekly/daily/hourly lag that can be impactful to today as well? So I know a 2 month lag is important, but can I see if 3 weeks ago lag is also important?
Months and weeks are on different time scales, and the customer has data given in minutes. But they want to know which time scale would be the most important for their time series model: yearly, quarterly, monthly, weekly. AND if its possible for a time series model to use lag points from different time scales.
Thank you,
lovy
