The Large-Sample Behavior of Transformations to Normality
正态化变换的大样本行为
We investigate the large-sample behavior of the Box-Cox procedures for selecting a transformation to normality. The study of the large-sample behavior clearly reveals the role played by the assumptions. Based on our large-sample results, we introduce an information number approach for transforming a known distribution to near normality. This latter procedure provides bench marks for the maximum amount of improvement achievable through power transformations. We illustrate our…