Forecast a model from the fable package

Produces forecasts from a trained model.

# S3 method for model_mean
forecast(
  object,
  new_data,
  specials = NULL,
  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()).
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 when bootstrap = TRUE.
...	Additional arguments for forecast model methods.

Value

A list of forecasts.

Examples

library(tsibbledata)
vic_elec %>%
  model(avg = MEAN(Demand)) %>%
  forecast()
#> # A fable: 4 x 4 [30m] <Australia/Melbourne>
#> # Key:     .model [1]
#>   .model Time                         Demand .mean
#>   <chr>  <dttm>                       <dist> <dbl>
#> 1 avg    2015-01-01 00:00:00 N(4665, 764369) 4665.
#> 2 avg    2015-01-01 00:30:00 N(4665, 764369) 4665.
#> 3 avg    2015-01-01 01:00:00 N(4665, 764369) 4665.
#> 4 avg    2015-01-01 01:30:00 N(4665, 764369) 4665.