Transformations are useful when you want to stabilize the time series before computing the similarity measures. 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,

is the logistic transformation,

where the scaling factor is

and is the smallest integer greater than or equal to x.
is the square root transformation,

is the BoxCox transformation,

is the transformation computed by a userdefined subroutine that is created by using the FCMP procedure, where UserDefined is the subroutine name.
Other time series transformations can be performed prior to invoking the SIMILARITY procedure by using the SAS/ETS EXPAND procedure or the DATA step.