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 ETS
generate(x, new_data, specials, bootstrap = FALSE, ...)

Arguments

x

A fitted model.

new_data

A tsibble containing the time points and exogenous regressors to produce forecasts for.

specials

(passed by fabletools::forecast.mdl_df()).

bootstrap

If TRUE, then forecast distributions are computed using simulation with resampled errors.

...

Other arguments passed to methods

See also

fabletools::generate.mdl_df

Examples

as_tsibble(USAccDeaths) %>%
  model(ETS(log(value) ~ season("A"))) %>%
  generate(times = 100)
#> # A tsibble: 2,400 x 4 [1M]
#> # Key:       .model, .rep [100]
#>    .model                            .rep     index   .sim
#>    <chr>                             <chr>    <mth>  <dbl>
#>  1 "ETS(log(value) ~ season(\"A\"))" 1     1979 Jan  8540.
#>  2 "ETS(log(value) ~ season(\"A\"))" 1     1979 Feb  7699.
#>  3 "ETS(log(value) ~ season(\"A\"))" 1     1979 Mar  8701.
#>  4 "ETS(log(value) ~ season(\"A\"))" 1     1979 Apr  8844.
#>  5 "ETS(log(value) ~ season(\"A\"))" 1     1979 May 10054.
#>  6 "ETS(log(value) ~ season(\"A\"))" 1     1979 Jun 10151.
#>  7 "ETS(log(value) ~ season(\"A\"))" 1     1979 Jul 10225.
#>  8 "ETS(log(value) ~ season(\"A\"))" 1     1979 Aug 10220.
#>  9 "ETS(log(value) ~ season(\"A\"))" 1     1979 Sep  8826.
#> 10 "ETS(log(value) ~ season(\"A\"))" 1     1979 Oct  8670.
#> # ℹ 2,390 more rows