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.

Value

A 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

as_tsibble(USAccDeaths) %>% model(lm = TSLM(log(value) ~ trend() + season()))
#> # A mable: 1 x 1 #> lm #> <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