The Box-Cox transformation is a general class of transformations that includes the logarithm as a special case. The %BOXCOXAR macro can be used to find an optimal Box-Cox transformation for a time series. See Chapter 5 for more information about the %BOXCOXAR macro.

The logistic transformation is useful for variables with both an upper and a lower bound, such as market shares. The logistic transformation is useful for proportions, percent values, relative frequencies, or probabilities. The logistic function transforms values between 0 and 1 to values that can range from - to +.

For example, the following statements transform the variable SHARE from percent values to an unbounded range:

   data a;
      set a;
      lshare = log( share / ( 100 - share ) );
   run;

Many other data transformation can be used. You can create virtually any desired data transformation using DATA step statements.