tsclean: Identify and replace outliers and missing values in a time series
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
tsclean(x, replace.missing = TRUE, lambda = NULL)
If TRUE, it not only replaces outliers, but also
interpolates missing values
Box-Cox transformation parameter. If lambda="auto",
then a transformation is automatically selected using BoxCox.lambda.
The transformation is ignored if NULL. Otherwise,
data transformed before model is estimated.