Multivariate Box-Cox transformations with applications to neurometric data.

The Box-Cox power transform methodology for achieving Gaussianity is developed for a variety of models useful in neurometric statistical analysis. Algorithms are proposed for estimating the optimal transformations in the univariate and multivariate cases. Their use is briefly illustrated with neurometric data.