论文标题
在多元两样本问题的置换测试中使用sindhorn差异
Using the Sinkhorn divergence in permutation tests for the multivariate two-sample problem
论文作者
论文摘要
为了使Wasserstein的距离适应大型样本多元非参数两样本问题，使其在计算上可行，基于与数据相关分区相关的概率向量之间的sindhorn差异进行了置换测试。评估实施这些测试的不同方式，并在某些情况下确定了基本统计量的渐近分布。在模拟示例中比较了提出的统计数据，与Schilling的测试是文献中最佳的非参数测试之一。
In order to adapt the Wasserstein distance to the large sample multivariate non-parametric two-sample problem, making its application computationally feasible, permutation tests based on the Sinkhorn divergence between probability vectors associated to data dependent partitions are considered. Different ways of implementing these tests are evaluated and the asymptotic distribution of the underlying statistic is established in some cases. The statistics proposed are compared, in simulated examples, with the test of Schilling's, one of the best non-parametric tests available in the literature.
