Produces forecasts from a trained model.
Usage
# S3 method for BINNET
forecast(object, new_data, specials = NULL, simulate = TRUE, times = 5000, ...)Arguments
- object
A model for which forecasts are required.
- new_data
A tsibble containing the time points and exogenous regressors to produce forecasts for.
- specials
(passed by
fabletools::forecast.mdl_df()).- simulate
If
TRUE, then forecast distributions are computed using simulation from a Bernoulli model.- times
The number of sample paths to use in estimating the forecast distribution when
simulate = TRUE.- ...
Other arguments passed to methods
Examples
melb_rain |>
model(nn = BINNET(Wet ~ fourier(K = 1, period = "year"))) |>
forecast(times = 10)
#> # A fable: 14 x 4 [1D]
#> # Key: .model [1]
#> .model Date Wet .mean
#> <chr> <date> <dist> <dbl>
#> 1 nn 2011-11-01 sample[10] 0.3
#> 2 nn 2011-11-02 sample[10] 0.3
#> 3 nn 2011-11-03 sample[10] 0.1
#> 4 nn 2011-11-04 sample[10] 0.4
#> 5 nn 2011-11-05 sample[10] 0.5
#> 6 nn 2011-11-06 sample[10] 0.2
#> 7 nn 2011-11-07 sample[10] 0.5
#> 8 nn 2011-11-08 sample[10] 0.4
#> 9 nn 2011-11-09 sample[10] 0.4
#> 10 nn 2011-11-10 sample[10] 0.4
#> 11 nn 2011-11-11 sample[10] 0.3
#> 12 nn 2011-11-12 sample[10] 0.6
#> 13 nn 2011-11-13 sample[10] 0.3
#> 14 nn 2011-11-14 sample[10] 0.4