Man pages for xavierkamp/tsForecastR
Forecasting with Traditional Time Series and Machine Learning Models
| add_features | Add features |
| add_placeholders | Add empty placeholders |
| add_timesteps | Add timesteps |
| check_backtesting_iter | Check backtesting iteration number |
| check_backtesting_opt | Check backtesting options |
| check_colnames | Drop punctuations in colnames |
| check_data_dir | Check the filepath where forecasts can be saved |
| check_data_sv_as_xts | Check the time series data and convert to xts |
| check_fc_horizon | Check forecasting horizon |
| check_model_names | Check model names |
| check_models_args | Check models' arguments |
| check_nb_cores | Check the number of selected CPU cores |
| check_period_iter | Check the period identifier |
| check_preprocess_fct | Check the custom preprocessing function |
| check_tensorflow | Check if tensorflow is properly installed |
| check_time_id | Check the time identifier |
| check_tmp_test_set_size | Check optional test set size |
| check_valid_set_size | Check validation set size |
| collapse_model_par | Store model estimates as a string |
| combine_fc_results | Combine forecasting info |
| default_prepro_fct | Default preprocessing function |
| extract_coef_arima | Extract model estimates for ARIMA |
| extract_coef_ets | Extract model estimates for ETS |
| extract_coef_nnetar | Extract model estimates for NNETAR |
| extract_coef_snaive | Extract model estimates for seasonal naive |
| extract_coef_stl | Extract model estimates for STL |
| extract_coef_tbats | Extract model estimates for TBATS |
| format_historical_data | Format original data |
| generate_fc | Forecasting Engine API |
| generate_fc_arima | ARIMA Model |
| generate_fc_automl_h2o | Automated Machine Learning |
| generate_fc_bsts | Bayesian Structural Time Series Model |
| generate_fc_ets | Exponential Smoothing Model |
| generate_fc_lstm_keras | Long-Short Term Memory Network |
| generate_fc_nnetar | Neural Network |
| generate_fc_snaive | Seasonal Naive Model |
| generate_fc_stl | Season-Trend Decomposition with Loess Model |
| generate_fc_tbats | TBATS Model |
| get_fc_with_PI | Extract forecasts and prediction intervals from list |
| get_split_keys | Get split keys |
| ini_model_output | Initialize the model output |
| nb_diffs | Determine the number of differencing to obtain a stationary... |
| normalize_data | Normalize the data |
| preprocess_custom_fct | Customized preprocessing function |
| print_model_name | Print to console the model name currently selected |
| read_fc_from_file | Read results from files |
| read_tsForecastR | Recursive function to read results from tsForecastR object |
| reshape_X | Reshape regressors X |
| reshape_Y | Reshape target variable y |
| save_as_df | Read forecasts from tsForecastR object |
| save_fc_bsts | Save forecasts (for bsts.prediction objects) |
| save_fc_forecast | Save forecasts (for forecast objects) |
| save_fc_ml | Save forecasts (for Machine Learning models) |
| split_train_test_set | Split the data into a training, validation and test set |
| transform_data | Apply a transformation on the data |
| univariate_xts | Extract a univariate xts object from a mutivariate 'xts'... |
| valid_md_arima | Check ARIMA model validity |
| valid_md_autml_h2o | Check AutoML-h2o model validity |
| valid_md_bsts | Check BSTS model validity |
| valid_md_ets | Check ETS model validity |
| valid_md_lstm_keras | Check LSTM-keras model validity |
| valid_md_nnetar | Check Neural Net model validity |
| valid_md_snaive | Check seasonal-naive model validity |
| valid_md_stl | Check STL model validity |
| valid_md_tbats | Check TBATS model validity |
