Fit a time series model using ets and
make forecasts. The frequency of the data is set a priori, as opposed to
estimating the parameter from the data.
ets_one_step uses ets to fit an
exponential-smoothing time series model and make a single one-step
forecast.
ets_ts(timeseries, num_ahead = 5, level = 95, frequency = 1) ets_one_step(timeseries, level = 95)
| timeseries | the time series to forecast |
|---|---|
| num_ahead | the number of points at the end of the time series to forecast |
| level | Confidence level for prediction intervals. |
| frequency | the number of observations per unit of time. |
a data.frame of the mean forecasts, the observed values, and the lower and upper CI levels (if an error occurs, then just NA values)