Man pages for fnoorian/mltsp
Tools for machine-learning based time-series prediction
| aggregate_xts | Aggregate data to the given time granularity |
| aggregate_xts_matrix | Aggregate xts matrix data to the given time granularity |
| binary_day_of_week_matrix | Create dummy variables for day of week |
| binary_hour_matrix | Create dummy variables for hour of day |
| build_mltsp_pipline | Create an ML TSP pipeline object |
| build_narx | Build a nonlinear auto-regressive time-series forecasting... |
| centered_lagged_windows | Create Centers the lag winow around Lag 0, with width p on... |
| clone_timestamps | Change values in a time-series |
| continue_timestamps | Continue the given time-stamps for the next 'h' steps |
| continue_timestamps_using_reference | Continue the given time-stamps for the next 'h' steps using a... |
| create_cv_timeslices | Create time-slices for time-series cross-validation |
| create_daily_xts | Aggregate data to a daily time-series |
| create_hourly_xts | Aggregate data to a hourly time-series |
| create_minutely_xts | Aggregate data to a minutely time-series |
| forecast.mltsp | Machine learning pipeline forecast |
| forecast.narx | Forecast a NARX object |
| lagmatrix | Collects and embeds lagged windows of data. |
| lag_windows | Collects and embeds lagged windows of data as a vector. |
| mltsp | Create an ML TSP object |
| mltsp_forecaster | Functional version of the mlts |
| narx | Nonlinear auto-regressive time-series forecasting with... |
| period.apply.string | Period apply with string function |
| period.first | Period apply with string function |
| period.last | Period apply with string function |
| predict.narx | Predict a time-series using a NARX object |
| seasonal_lag_windows | Creates a window around each seasonal lag, with... |
| SimpleLM | A Simple linear model. |
| ts_append | Appends new values to a time-series. |
| ts_continue | Create a bew time-series with the new value that continues... |
| ts_crossval | Time-series cross-validation |
| ts_crossval_simple | Simple time-series cross-validation |
| ts_inv_preprocess | Inverse preprocessing of a time-series |
| ts_preprocess | Preprocess a time-series |
