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Bahadur exact slopes of some tests for spectral densities

机译:Bahadur光谱密度测试的精确斜率

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摘要

The large deviation result is proved for two functionals of the empirical spectral process in zero-mean Gaussian stationary processes. As a statistical application, we deal with the Bahadur asymptotic efficiencies of two statistics for testing H: f_1 = f (specified), which are spectral analogue to the Kolmogorov-Smirnov (KS) and Kuiper statistics for testing hypothesis about distribution function in the iid setting. It is shown that the Kuiper type statistic is superior to the KS type statistic in terms of the Bahadur exact slope. We also discuss the a ( ≥ 2)-sample problem. Especially, for the two-sample problem, we investigate the Bahadur asymptotic efficiencies of several statistics for testing not only the goodness-of-fit hypothesis H_1: f_1 = f_2 = f (specified) but also the homogeneity hypothesis H_2 : f_1 = f_2 (unspecified).
机译:在零均值高斯平稳过程中,经验谱过程的两个函数证明了较大的偏差结果。作为统计应用,我们处理两种用于检验H的统计量的Bahadur渐近效率:f_1 = f(指定),它们与Kolmogorov-Smirnov(KS)和Kuiper统计量的频谱相似,用于检验关于iid中分布函数的假设设置。结果表明,就Bahadur精确斜率而言,Kuiper型统计量优于KS型统计量。我们还将讨论一个(≥2)样本问题。特别是对于两样本问题,我们研究了几种统计的Bahadur渐近效率,它们不仅用于检验拟合优度假设H_1:f_1 = f_2 = f(已指定),而且还用于检验同质性假设H_2:f_1 = f_2(未指定)。

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