Simulates future paths from a dataset using a fitted model. Innovations are
sampled by the model's assumed error distribution. If bootstrap
is TRUE
,
innovations will be sampled from the model's residuals. If new_data
contains the .innov
column, those values will be treated as innovations.
# S3 method for class 'TSLM'
generate(x, new_data, specials, bootstrap = FALSE, ...)
A fitted model.
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.
Other arguments passed to methods
as_tsibble(USAccDeaths) %>%
model(lm = TSLM(log(value) ~ trend() + season())) %>%
generate()
#> # A tsibble: 24 x 3 [1M]
#> # Key: .model [1]
#> .model index .sim
#> <chr> <mth> <dbl>
#> 1 lm 1979 Jan 8641.
#> 2 lm 1979 Feb 7267.
#> 3 lm 1979 Mar 7193.
#> 4 lm 1979 Apr 8260.
#> 5 lm 1979 May 8655.
#> 6 lm 1979 Jun 8968.
#> 7 lm 1979 Jul 10373.
#> 8 lm 1979 Aug 9256.
#> 9 lm 1979 Sep 8500.
#> 10 lm 1979 Oct 8165.
#> # ℹ 14 more rows