Refit a NNETAR model

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

lung_deaths_male <- as_tsibble(mdeaths)
lung_deaths_female <- as_tsibble(fdeaths)

fit <- lung_deaths_male %>%
  model(NNETAR(value))

report(fit)
#> 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