Box Cox Transformation. Box cox transformation was first developed by two british statisticians namely george box and sir david cox. The box cox transformation is named after statisticians george box and sir david roxbee cox who collaborated on a 1964 paper and developed the technique.
The basic idea behind this method is to find some value for λ such that the transformed data is as close to normally distributed as possible using the following formula. If one of the sample values is not positive then we add 1 a to all the sample values where a is the smallest sample value. Mathematics behind box cox transformation.
If one of the sample values is not positive then we add 1 a to all the sample values where a is the smallest sample value.
This will transform the sample into only positive values. The box cox transformation of the variable x is also indexed by λ and is defined as equation 1 at first glance although the formula in equation 1 is a scaled version of the tukey transformation x λ this transformation does not appear to be the same as the tukey formula in equation 2. Normality is an important assumption for many statistical techniques. A box cox transformation is a commonly used method for transforming a non normally distributed dataset into a more normally distributed one.
