Gluonts DeepAR

Time series forecasting occurs when you make scientific predictions based on historical time stamped data . It involves building models through historical analysis and using them to make observations and drive future strategic decision-making.

The forecast horizon is the length of time into the future for which forecasts are to be prepared . These generally vary from short-term forecasting horizons (less than three months) to long-term horizons (more than two years).

Multistep-ahead prediction is the task of predicting a sequence of values in a time series . A typical approach, known as multi-stage prediction, is to apply a predictive model step-by-step and use the predicted value of the current time step to determine its value in the next time step.

One-step ahead forecasts are computed sequentially for each data point by using computed level and trend states for the current point, and seasonal states for the last seasonal period . Forecast error is computed by subtracting forecast value at the previous point from the observed value at the current point.