The model formula will be handled using stats::model.matrix(), and so the the same approach to include interactions in stats::lm() applies when specifying the formula. In addition to stats::lm(), it is possible to include common_xregs in the model formula, such as trend(), season(), and fourier().

TSLM(formula)

Arguments

formula

Model specification.

Specials

xreg

Exogenous regressors can be included in an ARIMA model without explicitly using the xreg() special. Common exogenous regressor specials as specified in common_xregs can also be used. These regressors are handled using stats::model.frame(), and so interactions and other functionality behaves similarly to stats::lm().
xreg(...)
...
Bare expressions for the exogenous regressors (such as
log(x))

See also

Examples

USAccDeaths %>% as_tsibble %>% model(TSLM(log(value) ~ trend() + season()))
#> # A mable: 1 x 1 #> `TSLM(log(value) ~ trend() + season())` #> <model> #> 1 <TSLM>
library(tsibbledata) olympic_running %>% model(TSLM(Time ~ trend())) %>% interpolate(olympic_running)
#> # A tsibble: 312 x 4 [4Y] #> # Key: Length, Sex [14] #> Length Sex Year Time #> <int> <chr> <int> <dbl> #> 1 100 men 1896 12 #> 2 100 men 1900 11 #> 3 100 men 1904 11 #> 4 100 men 1908 10.8 #> 5 100 men 1912 10.8 #> 6 100 men 1916 10.8 #> 7 100 men 1920 10.8 #> 8 100 men 1924 10.6 #> 9 100 men 1928 10.8 #> 10 100 men 1932 10.3 #> # … with 302 more rows