This means that, for example, es() would return only one aggregated point forecast for the lead time h and similar things for upper bound of prediction interval. This then can be used for ordering policy etc.
A connected thing - cost function based on cumulative forecasts. Should be used if we are interested in inventory control, as it decreases safety stock.
Not really possible to do because of the contradiction between the multiplicative errors and the idea of cumulative forecasts. Currently simulation is used for all types of intervals here.
graphmaker() is updated in 3f8643e971f0771a2df334bb5a2e7b48672f302e
This means that, for example, es() would return only one aggregated point forecast for the lead time h and similar things for upper bound of prediction interval. This then can be used for ordering policy etc.
A connected thing - cost function based on cumulative forecasts. Should be used if we are interested in inventory control, as it decreases safety stock.