# Box-Cox Tab

The Box-Cox transformation has the following options.

Option | Description
--- | ---
Box-Cox transformation | Select this option to compute the Box-Cox transformation for each variable. The Box-Cox transformation transforms the original variable so that the new variable has a distribution that is as close to normality as possible.
Max. number of iterations | Use this option to specify the maximum number of iterations that can be used by the algorithm for finding a suitable Box-Cox transformation for each and every selected variable and on a by group basis (provided you have selected at least one by grouping variable).
Start lambda | Use this option to specify the minimum value of λ to start with.
End lambda | Use this option to specify the maximum value of λ to be tried by the search algorithm.
Epsilon | The search for optimal λ (and, hence, the best Box-Cox transformation) needs a convergence criterion, which is used to decide whether λ the algorithm has found a solution with reasonable accuracy. If convergence is achieved before the maximum number of iterations is reached, the algorithm stops. This feature is particularly useful when dealing with many variables and large data sets as it can save you time in producing your Box-Cox model(s).
Auto-shift variables <= 0 | Select this check box to shift the variables with value <= 0.
Shift variable to value | This option enables you to specify the value of the shift parameter of the Box-Cox transformation.

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