| add_index | Adds a sequential index column to a data frame |
| arima_string | Print the ARIMA model parameters |
| bats_string | Print the BATS model parameters |
| bike_sales | Fictional sales data for bike shops purchasing Cannondale bikes |
| sweep_package | sweep: Extending broom to time series forecasting |
| sw_augment | Augment data according to a tidied model |
| sw_augment.Arima | Tidying methods for ARIMA modeling of time series |
| sw_augment.bats | Tidying methods for BATS and TBATS modeling of time series |
| sw_augment.default | Default augment method |
| sw_augment.ets | Tidying methods for ETS (Error, Trend, Seasonal) exponential smoothing modeling of time series |
| sw_augment.HoltWinters | Tidying methods for HoltWinters modeling of time series |
| sw_augment.nnetar | Tidying methods for Nural Network Time Series models |
| sw_augment.stlm | Tidying methods for STL (Seasonal, Trend, Level) decomposition of time series |
| sw_augment.StructTS | Tidying methods for StructTS (Error, Trend, Seasonal) / exponential smoothing modeling of time series |
| sw_augment_columns | Augments data |
| sw_glance | Construct a single row summary "glance" of a model, fit, or other object |
| sw_glance.Arima | Tidying methods for ARIMA modeling of time series |
| sw_glance.bats | Tidying methods for BATS and TBATS modeling of time series |
| sw_glance.default | Default glance method |
| sw_glance.ets | Tidying methods for ETS (Error, Trend, Seasonal) exponential smoothing modeling of time series |
| sw_glance.HoltWinters | Tidying methods for HoltWinters modeling of time series |
| sw_glance.nnetar | Tidying methods for Nural Network Time Series models |
| sw_glance.stlm | Tidying methods for STL (Seasonal, Trend, Level) decomposition of time series |
| sw_glance.StructTS | Tidying methods for StructTS (Error, Trend, Seasonal) / exponential smoothing modeling of time series |
| sw_sweep | Tidy forecast objects |
| sw_tidy | Tidy the result of a time-series model into a summary tibble |
| sw_tidy.Arima | Tidying methods for ARIMA modeling of time series |
| sw_tidy.bats | Tidying methods for BATS and TBATS modeling of time series |
| sw_tidy.default | Default tidying method |
| sw_tidy.ets | Tidying methods for ETS (Error, Trend, Seasonal) exponential smoothing modeling of time series |
| sw_tidy.HoltWinters | Tidying methods for HoltWinters modeling of time series |
| sw_tidy.nnetar | Tidying methods for Nural Network Time Series models |
| sw_tidy.stl | Tidying methods for STL (Seasonal, Trend, Level) decomposition of time series |
| sw_tidy.stlm | Tidying methods for ARIMA modeling of time series |
| sw_tidy.StructTS | Tidying methods for StructTS (Error, Trend, Seasonal) / exponential smoothing modeling of time series |
| sw_tidy_decomp | Coerces decomposed time-series objects to tibble format. |
| sw_tidy_decomp.bats | Tidying methods for BATS and TBATS modeling of time series |
| sw_tidy_decomp.decomposed.ts | Tidying methods for decomposed time series |
| sw_tidy_decomp.ets | Tidying methods for ETS (Error, Trend, Seasonal) exponential smoothing modeling of time series |
| sw_tidy_decomp.HoltWinters | Tidying methods for HoltWinters modeling of time series |
| sw_tidy_decomp.stl | Tidying methods for STL (Seasonal, Trend, Level) decomposition of time series |
| sw_tidy_decomp.stlm | Tidying methods for STL (Seasonal, Trend, Level) decomposition of time series |
| tbats_string | Print the TBATS model parameters |
| tidiers_arima | Tidying methods for ARIMA modeling of time series |
| tidiers_bats | Tidying methods for BATS and TBATS modeling of time series |
| tidiers_decomposed_ts | Tidying methods for decomposed time series |
| tidiers_ets | Tidying methods for ETS (Error, Trend, Seasonal) exponential smoothing modeling of time series |
| tidiers_HoltWinters | Tidying methods for HoltWinters modeling of time series |
| tidiers_nnetar | Tidying methods for Nural Network Time Series models |
| tidiers_stl | Tidying methods for STL (Seasonal, Trend, Level) decomposition of time series |
| tidiers_StructTS | Tidying methods for StructTS (Error, Trend, Seasonal) / exponential smoothing modeling of time series |
| validate_index | Validates data frame has column named the same name as variable rename_index |