Box-Cox TransformationΒΆ

Box-Cox Transformation algorithm is a useful data pre-processing technique. It can be used to make the non-normally distributed data normal and stabilise variance of the time series data that is non-stationary in variance.

Input Parameters

Parameter Type Constraint Description Remarks
\(Y\) \(Y \in \mathbb R^N\) \(N \in \mathbb{N}, Y > 0\) Input data vector of length \(N\) None

Output Parameters

Parameter Type Constraint Description Remarks
\(\hat{Y}\) \(\hat{Y} \in \mathbb R^N\) \(N \in \mathbb{N}\) Data vector of length \(N\) that has approximately normal distribution None
\(\lambda\) \(\lambda \in \mathbb R\) None Estimated transformation parameter In some cases, it may be given by the user as an input parameter

Single Steps using the Algorithm

References