The default methods for impute_errors
are na.approx
, na.interp
, na_interpolation
, na.locf
, and na_mean
. See the help file for each for additional documentation. Additional arguments for the imputation functions are passed as a list of lists to the addl_arg
argument, where the list contains one to many elements that are named by the methods
. The elements of the master list are lists with arguments for the relevant methods. See the examples.
A user-supplied function can also be passed to methods
as an additional imputation method. A character string indicating the path of the function must also be supplied to methodPath
. The path must point to a function where the first argument is the time series to impute.
An alternative error function can also be passed to errorParameter
if errorPath
is not NULL
. The function specified in errorPath
must have two arguments where the first is a vector for the observed time series and the second is a vector for the predicted time series.
The smps
argument indicates the type of sampling for generating missing data. Options are smps = 'mcar'
for missing completely at random and smps = 'mar'
for missing at random. Additional information about the sampling method is described in sample_dat
. The relevant arguments for smps = 'mar'
are blck
and blckper
which greatly affect the sampling method.
Infinite comparisons are removed with a warning if errorParameter = 'mape'
. This occurs if any of the observed values in the original time series are zero. Error estimates for such datasets are evaluated only for non-zero observations.