tsclean

0th

Percentile

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

Keywords
ts
Usage
tsclean(x, replace.missing = TRUE, lambda = NULL)
Arguments
x

time series

replace.missing

If TRUE, it not only replaces outliers, but also interpolates missing values

lambda

a numeric value giving the Box-Cox transformation parameter

Value

Time series

See Also

na.interp, tsoutliers, supsmu

Aliases
  • tsclean
Examples
# NOT RUN {
cleangold <- tsclean(gold)

# }
Documentation reproduced from package forecast, version 8.1, License: GPL (>= 3)

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