Produces forecasts from a trained model.

# S3 method for NNETAR
forecast(object, new_data, specials = NULL,
simulate = TRUE, bootstrap = FALSE, times = 1000, ...)

## 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()` ). |

simulate |
If `TRUE` , prediction intervals are produced by simulation rather than using analytic formulae. |

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 if simulated intervals are used. |

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

## Value

A list of forecasts.

## Examples

as_tsibble(airmiles) %>%
model(nn = NNETAR(box_cox(value, 0.15))) %>%
forecast(times = 10)

#> # A fable: 2 x 4 [1Y]
#> # Key: .model [1]
#> .model index value .distribution
#> <chr> <dbl> <dbl> <dist>
#> 1 nn 1961 31930. t(sim(=dbl[10]))
#> 2 nn 1962 32996. t(sim(=dbl[10]))