compute_prediction_statistics: Compute the prediction statistics
In bnaras/pip: Platelet Inventory Prediction

Description Usage Arguments Value

Compute three-day predicted usage, waste, remaining and shortage using the actual usage and predicted usage.

1 2	compute_prediction_statistics(y, t_pred, initial_expiry_data = c(0, 0), initial_collection_data = c(60, 60, 60), start = 10)

`y`	is the number of units used at the current day i
`t_pred`	is the sum of the predicted number of units for days i+1, i+2, i+3
`initial_expiry_data`	the number of units that can be used the current day and the next (2-length vector)
`initial_collection_data`	is the number of units to collect for days i, i+1, i+2
`start`	is when we start the clock. So for example, in this default invocation the shelf storage (initial_collection_data) was 60, 60, 60, on days 10, 11, and 12. So the evaluation of the model begins at day 11 but the decision to order collection starts on day 13.

a list with four components, x is the number of units to collect, r is a matrix of two columns indicating remaining units usable on day i+1 and day i+2, w is waste, and s is shortage.

bnaras/pip documentation built on May 5, 2019, 6:54 p.m.