Function reference • MATSSforecasting

Data Processing
`get_ward_data()`	Read in a specific database from Ward et al. 2014
`reshape_ward_data()`	Reshape the processed data file from Ward et al. 2014
Build Drake Plans
`build_ward_data_plan()`	Make a drake plan with all the datasets in Ward et al. 2014
`build_ward_methods_plan()`	Make a drake plan with all the forecasting methods in Ward et al. 2014
Forecasting Functions
`arima_ts()` `arfima_ts()` `autoarima_one_step()` `arfima_one_step()`	Make forecasts using AR / ARIMA
`ets_ts()` `ets_one_step()`	Exponentially smoothed time series model
`gam_ts()`	Make forecasts using a Generalized Additive Model
`gausspr_ts()`	Make forecasts using gaussian process regression
`lm_ts()`	Make forecasts using a Linear Model
`locreg_ts()`	Make forecasts using locally weighted regression
`marss_ts()` `marss_rw_one_step()`	Make forecasts using a state space model
`nnet_ts()`	Make forecasts using neural network time series model
`npreg_ts()`	Make forecasts using nonparametric kernel regression
`ranfor_ts()`	Make forecasts using a random forest model
`simplex_ts()` `smap_ts()` `simplex_one_step()` `smap_one_step()`	Make forecasts using simplex projection or S-maps
Forecasting Utilities
`forecast_iterated()`	Iterated one-step forecasting (no refitting)
`hindcast()`	Hindcasting with one-step forecasts
Testing Utilities
`expect_NA_warnings()`	Check if warnings are expected for a too-short time series
`expect_forecasts()`	Check if object is in valid forecasts format

Reference