Identify and replace outliers and missing values in a time series
Uses supsmu for non-seasonal series and a periodic stl decompostion with seasonal series to identify outliers. To estimate missing values and outlier replacements, linear interpolation is used on the (possibly seasonally adjusted) series
tsclean(x, replace.missing = TRUE, lambda = NULL)
- time series
- If TRUE, it not only replaces outliers, but also interpolates missing values
- a numeric value giving the Box-Cox transformation parameter
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