The function extracts 1 to h steps ahead forecast errors from the model.
Usage
rmultistep(object, h = 10, error = c("default", "additive",
"multiplicative"), ...)
Value
The matrix with observations in rows and h steps ahead values in columns.
So, the first row corresponds to the forecast produced from the 0th observation
from 1 to h steps ahead.
Arguments
object
Model estimated using one of the forecasting functions.
h
The forecasting horizon to use.
error
Defines what type of error to return. "default" means returning the
one used in the original model. "additive" is to return e_t = y_t - mu_t.
Finally, "multiplicative" will return e_t = (y_t - mu_t) / mu_t.
The errors correspond to the error term epsilon_t in the ETS models. Don't forget
that different models make different assumptions about epsilon_t and / or 1+epsilon_t.