What about all those zeroes? Measuring performance of models on intermittent demand

In one of the previous posts, we have discussed how to measure the accuracy of forecasting methods on the continuous data. All these MAE, RMSE, MASE, rMAE, rRMSE and other measures can give you an information about the mean or median performance of forecasting methods. We have also discussed how to measure the performance of […]

How confident are you? Assessing the uncertainty in forecasting

Introduction Some people think that the main idea of forecasting is in predicting the future as accurately as possible. I have bad news for them. The main idea of forecasting is in decreasing the uncertainty. Think about it: any event that we want to predict has some systematic components $$\mu_t$$, which could potentially be captured […]

Are you sure you’re precise? Measuring accuracy of point forecasts

Two years ago I have written a post “Naughty APEs and the quest for the holy grail“, where I have discussed why percentage-based error measures (such as MPE, MAPE, sMAPE) are not good for the task of forecasting performance evaluation. However, it seems to me that I did not explain the topic to the full […]

Naughty APEs and the quest for the holy grail

Today I want to tell you a story of naughty APEs and the quest for the holy grail in forecasting. The topic has already been known for a while in academia, but is widely ignored by practitioners. APE stands for Absolute Percentage Error and is one of the simplest error measures, which is supposed to […]