论文标题
功能数据中生物等效性的有效测试
Efficient tests for bio-equivalence in functional data
论文作者
论文摘要
我们研究了两个样本功能数据问题中功能参数（例如均值或方差函数）的等效性的问题。与以前的工作相反，通过比较每个点的功能，将功能问题减少到标量数据等效性的多个测试问题，我们的方法基于测量两个功能参数之间最大偏差的距离的估计值。如果最大偏差的估计值不超过给定阈值，则要求等价。提出了一个引导程序，以获取用于测试统计量的分布的分位数，并且在大型样本场景中证明了相应测试的一致性。由于这里提出的方法避免使用交叉点原理，它们比当前可用的方法不那么保守，更强大。
We study the problem of testing the equivalence of functional parameters (such as the mean or variance function) in the two sample functional data problem. In contrast to previous work, which reduces the functional problem to a multiple testing problem for the equivalence of scalar data by comparing the functions at each point, our approach is based on an estimate of a distance measuring the maximum deviation between the two functional parameters. Equivalence is claimed if the estimate for the maximum deviation does not exceed a given threshold. A bootstrap procedure is proposed to obtain quantiles for the distribution of the test statistic and consistency of the corresponding test is proved in the large sample scenario. As the methods proposed here avoid the use of the intersection-union principle they are less conservative and more powerful than the currently available methodology.
