Forecast a model from the fable package

Produces forecasts from a trained model.

# S3 method for ETS
forecast(
  object,
  new_data,
  specials = NULL,
  simulate = FALSE,
  bootstrap = FALSE,
  times = 5000,
  ...
)

Arguments

object	The time series model used to produce the forecasts
new_data	A tsibble containing future information used to forecast.
specials	(passed by fabletools::forecast.mdl_df()).
simulate	If TRUE, prediction intervals are produced by simulation rather than using analytic formulae.
bootstrap	If TRUE, then forecast distributions are computed using simulation with resampled errors.
times	The number of sample paths to use in estimating the forecast distribution if simulated intervals are used.
...	Additional arguments for forecast model methods.

Value

A list of forecasts.

Examples

as_tsibble(USAccDeaths) %>%
  model(ets = ETS(log(value) ~ season("A"))) %>%
  forecast()
#> # A fable: 24 x 4 [1M]
#> # Key:     .model [1]
#>    .model    index             value  .mean
#>    <chr>     <mth>            <dist>  <dbl>
#>  1 ets    1979 Jan   t(N(9, 0.0011))  8296.
#>  2 ets    1979 Feb t(N(8.9, 0.0014))  7524.
#>  3 ets    1979 Mar   t(N(9, 0.0018))  8366.
#>  4 ets    1979 Apr t(N(9.1, 0.0022))  8622.
#>  5 ets    1979 May t(N(9.2, 0.0026))  9532.
#>  6 ets    1979 Jun  t(N(9.2, 0.003)) 10049.
#>  7 ets    1979 Jul t(N(9.3, 0.0035)) 10976.
#>  8 ets    1979 Aug  t(N(9.2, 0.004)) 10252.
#>  9 ets    1979 Sep t(N(9.1, 0.0045))  9169.
#> 10 ets    1979 Oct  t(N(9.2, 0.005))  9499.
#> # … with 14 more rows