Man pages for nredell/forecastML
Time Series Forecasting with Machine Learning Methods
| calculate_intervals | Calculate bootstrap prediction intervals for forecasts |
| combine_forecasts | Combine multiple horizon-specific forecast models to produce... |
| create_lagged_df | Create model training and forecasting datasets with lagged,... |
| create_skeleton | Remove the features from a lagged training dataset to reduce... |
| create_windows | Create time-contiguous validation datasets for model... |
| data_buoy | NOAA buoy weather data |
| data_buoy_gaps | NOAA buoy weather data |
| data_seatbelts | Road Casualties in Great Britain 1969-84 |
| fill_gaps | Prepare a dataset for modeling by filling in temporal gaps in... |
| plot.forecast_error | Plot forecast error |
| plot.forecastML | Plot an object of class 'forecastML' |
| plot.forecast_model_hyper | Plot hyperparameters |
| plot.forecast_results | Plot an object of class forecast_results |
| plot.lagged_df | Plot datasets with lagged features |
| plot.training_results | Plot an object of class training_results |
| plot.validation_error | Plot validation dataset forecast error |
| plot.windows | Plot validation datasets |
| predict.forecast_model | Predict on validation datasets or forecast |
| reconcile_forecasts | Reconcile multiple temporal or hierarchical forecasts |
| residuals | Return model residuals |
| return_error | Compute forecast error |
| return_hyper | Return model hyperparameters across validation datasets |
| summary.lagged_df | Return a summary of a lagged_df object |
| train_model | Train a model across horizons and validation datasets |
