We are working with 3 years of 15minute time-interval media data (1million+ entries) and have 14 external regressors (daypart, weekdays, holiday, genres). Objective is to forecast for next 15-minute intervals for given values of external regressors. What we did: - Used auto.arima (with xreg) from forecast package on this data. Result attached
Created a sub-set of 5% of xreg data to check forecasting accuracy. When we compare actual media GRP values with forecasted values, there is high deviation of ~100% for certain data points.
- Is auto.arima the right approach for such large data?
- How can we improve accuracy of this model?