A semi-parametric method for transforming data to normality
Abstract
A non-parametric transformation function is introduced to transform data to any continuous distribution. When transformation of data to normality is desired, the use of a suitable parametric pre-transformation function improves the performance of the proposed non-parametric transformation function. The resulting semi-parametric transformation function is shown empirically, via a Monte Carlo study, to perform at least as well as any parametric transformation currently available in the literature.
URI
http://hdl.handle.net/10394/3085https://doi.org/10.1007/s11222-008-9053-3
https://link.springer.com/article/10.1007%2Fs11222-008-9053-3