
There are four transformations available for strictly positive series only. Let
be the original time series, and let
be the transformed series. The transformations are defined as follows:
is the logarithmic transformation.
![\[ w_{t} = \mr{ln}(y_{t}) \]](images/etsug_timeseries0013.png)
is the logistic transformation.
![\[ w_{t} = \mr{ln}(c y_{t} / (1-c y_{t})) \]](images/etsug_timeseries0014.png)
where the scaling factor
is
![\[ c = (1-10^{-6}) 10 ^{- \mr{ceil}( \mr{log}_{10}({max}( y_{t}) ))} \]](images/etsug_timeseries0016.png)
and
is the smallest integer greater than or equal to x.
is the square root transformation.
![\[ w_{t} = \sqrt {y_{t}} \]](images/etsug_timeseries0018.png)
is the Box-Cox transformation.
![\[ w_{t} = \begin{cases} \frac{y_{t}^{{\lambda }} - 1}{\lambda }, & {\lambda } {\ne } 0 \\ \mr{ln}(y_{t}), & {\lambda } = 0 \end{cases} \]](images/etsug_timeseries0019.png)
More complex time series transformations can be performed by using the EXPAND procedure of SAS/ETS.