论文标题
通过Rényi的pseudoDistance估计量，通过WALD型测试比较两个依赖的正常种群的强大方法
Robust approach for comparing two dependent normal populations through Wald-type tests based on Rényi's pseudodistance estimators
论文作者
论文摘要
由于Fisher（1915，1921）发表了两篇开创性论文，因此对双变量正态分布的固定值相关系数为NULL假设的测试构成了一个重要的统计问题。在渐近稳定统计的框架内，它仍然是一个引起人们兴趣的话题。为此，提出了针对配对相关的正常随机样品的，提出了Rényi的伪抗估计量，建立了它们的渐近分布，并为其计算提供了迭代算法。从他们那里构建了WALD型测试统计数据，这些统计数据是针对不同感兴趣的问题的，理论上研究了其影响功能。为了测试不同环境中的无效相关性，一项广泛的仿真研究和两个基于数据的示例支持我们提案的鲁棒性能。
Since the two seminal papers by Fisher (1915, 1921) were published, the test under a fixed value correlation coefficient null hypothesis for the bivariate normal distribution constitutes an important statistical problem. In the framework of asymptotic robust statistics, it remains being a topic of great interest to be investigated. For this and other tests, focused on paired correlated normal random samples, Rényi's pseudodistance estimators are proposed, their asymptotic distribution is established and an iterative algorithm is provided for their computation. From them the Wald-type test statistics are constructed for different problems of interest and their influence function is theoretically studied. For testing null correlation in different contexts, an extensive simulation study and two real data based examples support the robust properties of our proposal.
