m5_demand_type: Classify time series of the particular items

In m5: 'M5 Forecasting' Challenges Data

Classify time series of the particular items

Description

Each time series in the dataset can be assigned one of the following classes:

Usage

m5_demand_type(data)

Arguments

data	The result of the m5_prepare function; tiny_m5 can be passed as well.

Details

• Smooth (ADI < 1.32 and CV² < 0.49).

• Intermittent (ADI >= 1.32 and CV² < 0.49)

• Erratic (ADI < 1.32 and CV² >= 0.49)

• Lumpy (ADI >= 1.32 and CV² >= 0.49)

Value

A data.table containing item ids (item_id and store_id), ADI and CV2 scores (adi and cv2 respectively) as well as the final class chosen based on the aforementioned scores (demand_type).

References

Syntetos A. A. and Boylan J. E., 2005, The accuracy of intermittent demand estimates. International Journal of Forecasting 21: 303–314 Forecast Error Measures: Intermittent Demand

Examples

head(m5_demand_type(tiny_m5))

m5 documentation built on Sept. 12, 2022, 9:05 a.m.