Power of Tests for Nonlinear Transformation in Regression Analysis
比较了回归模型中因变量非线性变换检验的局部势，发现Cox检验优于其他两种检验，并通过蒙特卡洛实验验证了理论结果。
This paper compares the local power of tests for a nonlinear transformation of the dependent variable in a regression model against the alternative hypothesis of a linear transformation. It is shown that the local power of the Cox test is higher than those of the extended projection test of MacKinnon, White, and Davidson, and Bera and McAleer's test. The theoretical result is supported by a Monte-Carlo experiment in testing for a regression model with a logarithmically transformed dependent variable against a linear regression model.