Applies a fitted NNETAR model to a new dataset.

# S3 method for NNETAR
refit(object, new_data, specials = NULL, reestimate = FALSE, ...)

## 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()` ). |

reestimate |
If `TRUE` , the networks will be initialized with random
starting weights to suit the new data. If `FALSE` , for every network the best
individual set of weights found in the pre-estimation process is used as the
starting weight vector. |

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

## Value

A refitted model.

## Examples

#> Series: value
#> Model: NNAR(3,1,2)[12]
#>
#> Average of 20 networks, each of which is
#> a 4-2-1 network with 13 weights
#> options were - linear output units
#>
#> sigma^2 estimated as 21523

fit %>%
refit(new_data = lung_deaths_female, reestimate = FALSE) %>%
report()

#> Series: value
#> Model: NNAR(3,1,2)[12]
#>
#> Average of 20 networks, each of which is
#> a 4-2-1 network with 13 weights
#> options were - linear output units
#>
#> sigma^2 estimated as 236049