Function-based hypothesis testing in two-sample location-scale models has been addressed for uncensored data using the empirical characteristic function. A test of adequacy in censored two-sample location-scale models is lacking, however. A plug-in empirical likelihood approach is used to introduce a test statistic, which, asymptotically, is not distribution free. Hence for practical situations bootstrap is necessary for performing the test. A multiplier bootstrap and a model appropriate resampling procedure are given to approximate critical values from the null asymptotic distribution. Although minimum distance estimators of the location and scale are deployed for the plug-in, any consistent estimators can be used. Numerical studies are carried out that validate the proposed testing method, and real example illustrations are given.

中文翻译：

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审查了两个样本的位置比例模型中基于功能的假设检验。

使用经验特征函数，针对未经审查的数据解决了两个样本位置比例模型中基于函数的假设检验。但是，缺乏在审查的两个样本的地点规模模型中进行充分性测试的方法。插入式经验似然方法用于引入检验统计量，该统计量在渐近性上不是免费的。因此，在实际情况下，执行测试需要自举。给出了一个乘数自举和一个模型适当的重采样程序，以从零渐近分布中近似临界值。尽管为插件部署了位置和比例尺的最小距离估算器，但是可以使用任何一致的估算器。进行了数值研究，验证了所提出的测试方法，并给出了实际的例子说明。