Transforming the Dependent Variable in Regression Models
提出一种尺度不变的因变量变换族，可处理零值或负值变量，并推导两个拉格朗日乘子检验，用于检验无需变换的原假设。蒙特卡洛模拟和实证例子验证了方法。
A scale-invariant family of transformations is proposed which, unlike the Box-Cox transformation, can be applied to variables that are equal to zero or of either sign. Two Lagrange Multiplier tests are derived for testing the null hypothesis of no dependent variable transformation against the alternative of a transformation from this family. These tests do not require explicit specification of the transformation and are related to the RESET test. We discuss a model that uses a particular case of this transformation, based on sinh-1, in some detail. Monte Carlo results are given, and an empirical example is provided.