Produces forecasts from a trained model.
# S3 method for class 'VAR'
forecast(
object,
new_data = NULL,
specials = NULL,
bootstrap = FALSE,
times = 5000,
...
)
A model for which forecasts are required.
A tsibble containing the time points and exogenous regressors to produce forecasts for.
(passed by fabletools::forecast.mdl_df()
).
If TRUE
, then forecast distributions are computed using simulation with resampled errors.
The number of sample paths to use in estimating the forecast distribution when bootstrap = TRUE
.
Other arguments passed to methods
A list of forecasts.
lung_deaths <- cbind(mdeaths, fdeaths) %>%
as_tsibble(pivot_longer = FALSE)
lung_deaths %>%
model(VAR(vars(mdeaths, fdeaths) ~ AR(3))) %>%
forecast()
#> # A fable: 24 x 4 [1M]
#> # Key: .model [1]
#> .model index .distribution .mean[,"mdeaths"]
#> <chr> <mth> <dist> <dbl>
#> 1 VAR(vars(mdeaths, fdeaths) ~ AR(3)) 1980 Jan MVN[2] 1486.
#> 2 VAR(vars(mdeaths, fdeaths) ~ AR(3)) 1980 Feb MVN[2] 1445.
#> 3 VAR(vars(mdeaths, fdeaths) ~ AR(3)) 1980 Mar MVN[2] 1369.
#> 4 VAR(vars(mdeaths, fdeaths) ~ AR(3)) 1980 Apr MVN[2] 1340.
#> 5 VAR(vars(mdeaths, fdeaths) ~ AR(3)) 1980 May MVN[2] 1327.
#> 6 VAR(vars(mdeaths, fdeaths) ~ AR(3)) 1980 Jun MVN[2] 1349.
#> 7 VAR(vars(mdeaths, fdeaths) ~ AR(3)) 1980 Jul MVN[2] 1395.
#> 8 VAR(vars(mdeaths, fdeaths) ~ AR(3)) 1980 Aug MVN[2] 1442.
#> 9 VAR(vars(mdeaths, fdeaths) ~ AR(3)) 1980 Sep MVN[2] 1477.
#> 10 VAR(vars(mdeaths, fdeaths) ~ AR(3)) 1980 Oct MVN[2] 1495.
#> # ℹ 14 more rows
#> # ℹ 1 more variable: .mean[2] <dbl>