forecast (version 8.18)

tsoutliers: Identify and replace outliers in a time series

Description

Uses supsmu for non-seasonal series and a periodic stl decomposition with seasonal series to identify outliers and estimate their replacements.

Usage

tsoutliers(x, iterate = 2, lambda = NULL)

Value

index

Indicating the index of outlier(s)

replacement

Suggested numeric values to replace identified outliers

Arguments

x

time series

iterate

the number of iterations required

lambda

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.

Author

Rob J Hyndman

References

Hyndman (2021) "Detecting time series outliers" https://robjhyndman.com/hyndsight/tsoutliers/.

See Also

na.interp, tsclean

Examples

Run this code

data(gold)
tsoutliers(gold)

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