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A modified signed likelihood ratio test in elliptical structural models

机译:椭圆结构模型中改进的带符号似然比检验

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In this paper we deal with the issue of performing accurate testing inference on a scalar parameter of interest in structural errors-in-variables models. The error terms are allowed to follow a multivariate distribution in the class of the elliptical distributions, which has the multivariate normal distribution as special case. We derive a modified signed likelihood ratio statistic that follows a standard normal distribution with a high degree of accuracy. Our Monte Carlo results show that the modified test is much less size distorted than its unmodified counterpart. An application is presented.
机译:在本文中,我们处理在结构误差变量模型中对目标标量参数执行精确测试推断的问题。在椭圆分布的类别中,允许误差项遵循多元分布,在特殊情况下,该分布具有多元正态分布。我们以较高的准确性得出遵循标准正态分布的修正的带符号似然比统计量。我们的蒙特卡洛结果表明,与未修改的测试相比,修改后的测试的尺寸失真要小得多。提出了一个应用程序。

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