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

## Description

Uses supsmu for non-seasonal series and a robust STL decomposition for
seasonal series. To estimate missing values and outlier replacements,
linear interpolation is used on the (possibly seasonally adjusted) series

## Usage

tsclean(x, replace.missing = TRUE, lambda = NULL)

## Arguments

replace.missing

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

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.

## Examples

# NOT RUN {
cleangold <- tsclean(gold)
# }