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
If TRUE, it not only replaces outliers, but also
interpolates missing values
the number of iterations required
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.