Produces forecasts from a trained model.
# S3 method for ARIMA
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.
USAccDeaths %>%
as_tsibble() %>%
model(arima = ARIMA(log(value) ~ pdq(0, 1, 1) + PDQ(0, 1, 1))) %>%
forecast()
#> # A fable: 24 x 4 [1M]
#> # Key: .model [1]
#> .model index value .mean
#> <chr> <mth> <dist> <dbl>
#> 1 arima 1979 Jan t(N(9, 0.0014)) 8290.
#> 2 arima 1979 Feb t(N(8.9, 0.0018)) 7453.
#> 3 arima 1979 Mar t(N(9, 0.0022)) 8276.
#> 4 arima 1979 Apr t(N(9.1, 0.0025)) 8584.
#> 5 arima 1979 May t(N(9.2, 0.0029)) 9499.
#> 6 arima 1979 Jun t(N(9.2, 0.0033)) 9900.
#> 7 arima 1979 Jul t(N(9.3, 0.0037)) 10988.
#> 8 arima 1979 Aug t(N(9.2, 0.0041)) 10132.
#> 9 arima 1979 Sep t(N(9.1, 0.0045)) 9138.
#> 10 arima 1979 Oct t(N(9.1, 0.0049)) 9391.
#> # ℹ 14 more rows