A class of multivariate distribution-free tests of independence based on graphs.
A class of multivariate distribution-free tests of independence based on graphs.
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一类基于图形的独立性多元分布测试。
DOI：
10.1016/j.jspi.2012.06.003
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发表时间：
2012-12
影响因子：
0.9
通讯作者：
Heller, Y.
中科院分区：
文献类型：
--
作者：
Heller, R.;Gorfine, M.;Heller, Y.
针对两个响应坐标子集的独立性，提出了一类无分布检验。测试基于每个响应子集内受试者之间的成对距离。每个响应坐标的子集都是一个完整的图，样本点作为节点，成对距离作为边的权重。所提出的检验统计量仅依赖于这些完全图中边的秩序。响应向量可以是任何维度的。具体地，样本的数量可以小于响应的维度。在独立性的原假设下，检验统计量具有已知期望和方差的正态极限分布。给出了14个样本的检验统计量的精确分布自由零分布，并考虑了更大样本量的蒙特-卡罗近似。我们在模拟中证明，这类新的测试具有良好的电源性能非常一般的替代品。
A class of distribution-free tests is proposed for the independence of two subsets of response coordinates. The tests are based on the pairwise distances across subjects within each subset of the response. A complete graph is induced by each subset of response coordinates, with the sample points as nodes and the pairwise distances as the edge weights. The proposed test statistic depends only on the rank order of edges in these complete graphs. The response vector may be of any dimensions. In particular, the number of samples may be smaller than the dimensions of the response. The test statistic is shown to have a normal limiting distribution with known expectation and variance under the null hypothesis of independence. The exact distribution free null distribution of the test statistic is given for a sample of size 14, and its Monte-Carlo approximation is considered for larger sample sizes. We demonstrate in simulations that this new class of tests has good power properties for very general alternatives.
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DOI：
10.1214/09-aoas312
发表时间：
2009-01-01
期刊：
The annals of applied statistics
影响因子：
--
作者：
Kosorok MR
通讯作者：
Kosorok MR
影响因子：
64.5
作者：
Sakaue-Sawano, Asako;Kurokawa, Hiroshi;Miyawaki, Atsushi
通讯作者：
Miyawaki, Atsushi
影响因子：
1.9
作者：
Benjamini, Yoav;Heller, Ruth
通讯作者：
Heller, Ruth
DOI：
10.1111/j.2517-6161.1995.tb02031.x
发表时间：
1995-01-01
影响因子：
5.8
作者：
BENJAMINI, Y;HOCHBERG, Y
通讯作者：
HOCHBERG, Y
影响因子：
2.3
作者：
HALL, P
通讯作者：
HALL, P