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| Working with Time Series Data |
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 4 for more information on 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.
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