多变量定位问题的非参数深度测试

Pub Date : 2021-06-29 DOI:10.1111/anzs.12328
Sakineh Dehghan, Mohammad Reza Faridrohani
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引用次数: 2

摘要

本文利用数据深度的概念,描述了单样本定位问题的两类仿射不变检验统计量。这些测试是通过排列测试的思想实现的。对一些竞争对手的测试性能进行了广泛的模拟研究。可以观察到,与竞争对手相比,这些测试在广泛的替代方案中表现良好。如果提议的测试是基于无矩深度函数定义的,那么它本质上不需要具有任何阶的有限矩,并且测试比现有的一些测试具有更广泛的适用性。对所提出的测试方法进行了鲁棒性仿真研究。最后,我们将测试应用到一个真实的数据示例中。
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Non-parametric depth-based tests for the multivariate location problem

In this paper, using the notion of data depth, we describe two classes of affine invariant test statistics for the one-sample location problem. The tests are implemented through the idea of permutation tests. The performance of the test against some competitors is investigated with an extensive simulation study. It is observed that the tests perform well when compared to their competitors for a wide spectrum of alternatives. If the proposed test is defined based on a moment-free depth function, then it is not inherently required to have finite moments of any order and the tests have broader applicability than some of the existing tests. The robustness property of the proposed tests is considered with a simulation study. Finally, we apply the tests to a real data example.

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