  Box-Cox power transformation is a commonly used methodology to transform the
distribution of a non-normal data into a normal one. Estimation of the
transformation parameter is crucial in this methodology. In this study, the
estimation process is hold via a searching algorithm and is integrated into
well-known seven goodness of fit tests for normal distribution. An artificial
covariate method is also included for comparative purposes. Simulation studies
are implemented to compare the effectiveness of the proposed methods. The
methods are also illustrated on two different real life data applications.
Moreover, an R package AID is proposed for implementation.
