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 class '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                               index .rep    .sim
#>    <chr>                                <mth> <chr>  <dbl>
#>  1 "ETS(log(value) ~ season(\"A\"))" 1979 Jan 1      8244.
#>  2 "ETS(log(value) ~ season(\"A\"))" 1979 Feb 1      7226.
#>  3 "ETS(log(value) ~ season(\"A\"))" 1979 Mar 1      7913.
#>  4 "ETS(log(value) ~ season(\"A\"))" 1979 Apr 1      8342.
#>  5 "ETS(log(value) ~ season(\"A\"))" 1979 May 1      9437.
#>  6 "ETS(log(value) ~ season(\"A\"))" 1979 Jun 1      9440.
#>  7 "ETS(log(value) ~ season(\"A\"))" 1979 Jul 1     10092.
#>  8 "ETS(log(value) ~ season(\"A\"))" 1979 Aug 1      9126.
#>  9 "ETS(log(value) ~ season(\"A\"))" 1979 Sep 1      8183.
#> 10 "ETS(log(value) ~ season(\"A\"))" 1979 Oct 1      8750.
#> # ℹ 2,390 more rows