# tsoutliers

From forecast v8.9
by Rob Hyndman

##### Identify and replace outliers in a time series

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

- Keywords
- ts

##### Usage

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

##### Arguments

- x
time series

- iterate
the number of iteration only for non-seasonal series

- 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.

##### Value

Indicating the index of outlier(s)

Suggested numeric values to replace identified outliers

##### See Also

##### Examples

```
# NOT RUN {
data(gold)
tsoutliers(gold)
# }
```

*Documentation reproduced from package forecast, version 8.9, License: GPL-3*

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