tsclean {forecast} | R Documentation |
Identify and replace outliers and missing values in a time series
Description
Uses supsmu for non-seasonal series and a robust STL decomposition for seasonal series. To estimate missing values and outlier replacements, linear interpolation is used on the (possibly seasonally adjusted) series
Usage
tsclean(x, replace.missing = TRUE, iterate = 2, lambda = NULL)
Arguments
x |
time series |
replace.missing |
If TRUE, it not only replaces outliers, but also interpolates missing values |
iterate |
the number of iterations required |
lambda |
Box-Cox transformation parameter. If |
Value
Time series
Author(s)
Rob J Hyndman
References
Hyndman (2021) "Detecting time series outliers" https://robjhyndman.com/hyndsight/tsoutliers/.
See Also
Examples
cleangold <- tsclean(gold)
[Package forecast version 8.23.0 Index]