Generate new data from a fable model

Simulates future paths from a dataset using a fitted model. Innovations are sampled by the model's assumed error distribution. If bootstrap is TRUE, innovations will be sampled from the model's residuals. If new_data contains the .innov column, those values will be treated as innovations.

# S3 method for model_mean
generate(x, new_data, bootstrap = FALSE, ...)

Arguments

x	A fitted model.
new_data	A tsibble containing future information used to forecast.
bootstrap	If TRUE, then forecast distributions are computed using simulation with resampled errors.
...	Additional arguments for forecast model methods.

See also

fabletools::generate.mdl_df

Examples

library(tsibbledata)
vic_elec %>%
  model(avg = MEAN(Demand)) %>%
  generate()
#> # A tsibble: 4 x 4 [30m] <Australia/Melbourne>
#> # Key:       .model, .rep [1]
#>   .model Time                .rep   .sim
#>   <chr>  <dttm>              <chr> <dbl>
#> 1 avg    2015-01-01 00:00:00 1     5425.
#> 2 avg    2015-01-01 00:30:00 1     4485.
#> 3 avg    2015-01-01 01:00:00 1     4731.
#> 4 avg    2015-01-01 01:30:00 1     2698.