论文标题
基于内核的功能变量联合独立性
Kernel-based method for joint independence of functional variables
论文作者
论文摘要
这项工作调查了测试$ D $功能随机变量是否使用修改后的$ d $可变量Hilbert Schmidt Incepedence Criterion（$ D $ HSIC）的修改估计器是否共同独立的问题，该估计概述了$ d \ geq 2 $的情况。然后，我们在共同独立假设和替代假设下都获得该估计量的渐近正态性。一项模拟研究显示了在有限样品上提出的测试的良好性能。
This work investigates the problem of testing whether $d$ functional random variables are jointly independent using a modified estimator of the $d$-variable Hilbert Schmidt Indepedence Criterion ($d$HSIC) which generalizes HSIC for the case where $d \geq 2$. We then get asymptotic normality of this estimator both under joint independence hypothesis and under the alternative hypothesis. A simulation study shows good performance of the proposed test on finite sample.
