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A moment-based test for the homogeneity in mixture natural exponential family with quadratic variance functions

机译:具有二次方差函数的混合自然指数族均匀性的基于矩的检验

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摘要

In this paper, we propose a simple moment-based procedure for testing homogeneity in the natural exponential family with quadratic variance functions. In the literature, solutions to this problem normally involve establishing identifiability of parameters first, then testing the hypotheses whether the data come from a single distribution or a mixture of distributions. Our procedure directly tests the hypotheses without the need to establish parameter estimability. Simulation studies demonstrate that the power of our test is comparable to the Supplementary score test and the separate score test proposed by Wu and Gupta [Wu, Y., Gupta, A.K., 2003. Local score tests in mixture exponential family. J. Statist. Plann. Inference 116, 421-435], and the normalized score test proposed by Shoukri and Lathrop [Shoukri, M., Lathrop, G.M., 1993. Statistical testing of genetic linkage under heterogeneity. Biometrics 49, 151-161]. In these simulation studies, the methods by the others are specific to cases with a known null distribution, and our methods can also be applied to cases with unknown null distribution. Our test procedure is demonstrated on two real data sets.
机译:在本文中,我们提出了一个基于矩的简单方法,用于测试具有二次方差函数的自然指数族的同质性。在文献中,解决此问题的方法通常包括首先建立参数的可识别性,然后测试假设数据是来自单一分布还是混合分布。我们的过程无需建立参数可估计性即可直接测试假设。模拟研究表明,我们的测试能力可以与补充得分测试和Wu和Gupta提出的单独得分测试相媲美[Wu,Y.,Gupta,A.K.,2003。混合指数族中的本地得分测试。 J.统计学家。计划推论116、421-435]和Shoukri和Lathrop提出的归一化分数检验[Shoukri,M.,Lathrop,G.M.,1993。异质性下的遗传连锁统计检验。生物测定学49,151-161]。在这些模拟研究中,其他方法专用于已知零分布的情况,我们的方法也可以应用于未知零分布的情况。我们的测试程序在两个真实的数据集上得到了证明。

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