Box Cox Power Transformation. When λ 0. A box cox power transformation refers to a way of transforming response to satisfy the usual regression assumption of homogeneity and normality of variance.
Box cox transformation is one of the most challenging data transformation procedures and relatively more powerful than other forms of power transformation. Currently power transform supports the box cox transform and the yeo johnson transform. When some of the data are negative a shift parameter c needs to be added to all observations in the formulae above x is replaced with x c.
X λ log x when λ 0.
The regression model is therefore used to fit the transformed response. Box cox transformation is one of the most challenging data transformation procedures and relatively more powerful than other forms of power transformation. Formally a box cox transformation is defined as a way to transform non normal dependent variables in our data to a normal shape through which we can run a lot more tests than we could have. X λ x λ 1 λ.
