impute_modelled_data {tsrobprep}

Impute modelled missing time series data

Description

Returns a matrix or a list of matrices with imputed missing values or outliers. As argument the function requires an object of class "tsrobprep" and the quantiles to be imputed.

Usage

impute_modelled_data(object, tau = NULL)

Arguments

object

an object of class "tsrobprep" that is an output of function model_missing_data.

tau

the quantile(s) of the missing values to be imputed. tau should be a subset of the quantile values present in the "tsrobprep" object. By default all quantiles present in the object are used.

Value

A matrix or a list of matrices with imputed missing values or outliers. ⁠ ⁠

References

Narajewski M, Kley-Holsteg J, Ziel F (2021). “tsrobprep — an R package for robust preprocessing of time series data.” SoftwareX, 16, 100809. doi: 10.1016/j.softx.2021.100809.

See Also

model_missing_data, detect_outliers, auto_data_cleaning

Examples

## Not run: 
model.miss <- model_missing_data(
    data = GBload[,-1], S = c(48,7*48),
    no.of.last.indices.to.fix = dim(GBload)[1], consider.as.missing = 0,
    min.val = 0
)
model.miss$estimated.models
model.miss$replaced.indices
new.GBload <- impute_modelled_data(model.miss)

## End(Not run)