Usage
"forecast"(object, groups, len = 1, method = c("recurrent", "vector", "bootstrap-recurrent", "bootstrap-vector"), ..., drop = TRUE, drop.attributes = FALSE, cache = TRUE)
"forecast"(object, groups, len = 1, method = c("recurrent", "vector", "bootstrap-recurrent", "bootstrap-vector"), ..., drop = TRUE, drop.attributes = FALSE, cache = TRUE)
"predict"(object, groups, len = 1, method = c("recurrent", "vector", "bootstrap-recurrent", "bootstrap-vector"), ..., drop = TRUE, drop.attributes = FALSE, cache = TRUE)
"predict"(object, groups, len = 1, method = c("recurrent", "vector", "bootstrap-recurrent", "bootstrap-vector"), ..., drop = TRUE, drop.attributes = FALSE, cache = TRUE)
"predict"(object, groups, len = 1, method = c("recurrent-column", "recurrent-row", "vector-column", "vector-row"), ..., drop = TRUE, drop.attributes = FALSE, cache = TRUE)
Arguments
object
SSA object holding the decomposition
groups
list, the grouping of eigentriples to be used in the forecast
len
the desired length of the forecasted series
method
method of forecasting to be used. The confidence bounds
are available only for bootstrap-based methods
...
further arguments passed for forecast routines
(e.g. level
argument to bforecast
)
drop
logical, if 'TRUE' then the result is coerced to series
itself, when possible (length of 'groups' is one)
drop.attributes
logical, if 'TRUE' then the forecast routines do not try
to infer the time index arguments for the forecasted series.
cache
logical, if 'TRUE' then intermediate results will be
cached in the SSA object.