# tsclean

From forecast v5.3
by Rob Hyndman

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

Uses loess for non-seasonal series and a periodic stl decompostion with seasonal series to identify and replace outliers. To estimate missing values, linear interpolation is used for non-seasonal series, and a periodic stl decompostion is used with seasonal 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

##### Examples

```
data(gold)
tsclean(gold)
```

*Documentation reproduced from package forecast, version 5.3, License: GPL (>= 2)*

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