forecast_feature_matrix | Builds the exact training matrix the forecasting tools use: target (or one target per step ahead under the direct strategy), lags, rolling/seasonal/expanding/EWM statistics, calendar features and exogenous columns, after the target transforms, with incomplete leading rows dropped. | |
forecast_future_frame | The (series, period) rows of the next h periods after each series’ end: the rows future_exog must supply for dynamic exogenous columns. | |
forecast_exog_lags | Lags and per-series rolling/seasonal/expanding/EWM statistics of exogenous series (prices, rates, indicators), so a forecast can use their past values without needing their future ones. | |
forecast_calendar_features | Deterministic regressors for history and horizon: Fourier sine/cosine seasonality terms, a trend counter, calendar attributes of the dates, and known-in-advance columns shifted into history. | |
