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Uses supsmu for non-seasonal series and a periodic stl decomposition with seasonal series to identify outliers and estimate their replacements.
tsoutliers(x, iterate = 2, lambda = NULL)
time series
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.
Indicating the index of outlier(s)
Suggested numeric values to replace identified outliers
Hyndman (2021) "Detecting time series outliers" https://robjhyndman.com/hyndsight/tsoutliers/.
# NOT RUN {
data(gold)
tsoutliers(gold)
# }
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