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

## Arguments

x |
A fitted model. |

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. |

... |
Additional arguments for forecast model methods. |

## See also

## Examples

#> # A tsibble: 240 x 4 [1M]
#> # Key: .model, .rep [10]
#> .model index .rep .sim
#> <chr> <mth> <chr> <dbl>
#> 1 model 1979 Jan 1 8239.
#> 2 model 1979 Feb 1 8186.
#> 3 model 1979 Mar 1 8329.
#> 4 model 1979 Apr 1 8408.
#> 5 model 1979 May 1 8900.
#> 6 model 1979 Jun 1 9992.
#> 7 model 1979 Jul 1 11007.
#> 8 model 1979 Aug 1 10748.
#> 9 model 1979 Sep 1 9502.
#> 10 model 1979 Oct 1 10566.
#> # … with 230 more rows