This paper proposes a simple unified approach to testing transformations on cumulative distribution functions (CDFs) with nuisance parameters. We consider testing general parametric transformations on two CDFs, and then generalize the test for multiple CDFs. We construct the test using a numerical bootstrap method which can easily be implemented. The proposed test is shown to be asymptotically size controlled and consistent. Monte Carlo simulations and an empirical application show that the test performs well on finite samples.

翻译：本文件提出一种简单统一的方法,用麻烦参数测试累积分布函数(CDFs)的转换。我们考虑在两个CDF上测试一般参数转换,然后对多个CDF进行一般测试。我们使用易于执行的数字靴套方法构建测试。拟议的测试显示其大小在控制上和一致性。Monte Carlo模拟和实验应用显示,测试在有限的样本上运行良好。