I'm build a model where I need to account for seasonality, but the variable nature of Easter in particular is problematic.
I have about 7 years of sales data (at a weekly level), for 400 stores.
I'm not sure which approach would be best. ARIMA seems like a good option for accounting for Seasonality, but I'm struggling to account for Easter/Christmas and I'm not sure how I would go about levering the 400 parallel timeseries to improve the accuracy of the model.
Are there supervised learning functions that handle seasonality well, potentially using Easter and Christmas as boolean features?