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ON A POWER OF OPTIMAL TEST FOR ASYMPTOTIC DISTINCTION OF STATISTICAL HYPOTHESES FOR DISTRIBUTIONS WITH HEAVY TAILS

机译:重尾分布统计假设渐近区分的最优检验的幂

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摘要

In the paper, the asymptotic behavior of the power function of the most powerful test in the problem of testing a simple hypothesis against a simple alternative from a homogeneous sample of independent observations is studied under the assumption that the likelihood ratio has a heavy-tailed distribution belonging to the domain of attraction of a stable law.
机译:在本文中,在似然比具有重尾分布的假设下,研究了最强大的检验的幂函数的渐近行为,该检验在检验简单假设与独立观测值的均质样本中的简单备选方案有关的问题中属于稳定法律的吸引力领域。

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  • 来源
    《Journal of Mathematical Sciences》 |2015年第1期|18-26|共9页
  • 作者单位

    Lomonosov Moscow State University, Faculty of Computational Mathematics and Cybernetics, Moscow, Russia;

    Lomonosov Moscow State University, Faculty of Computational Mathematics and Cybernetics, Moscow, Russia,Institute of Informatics Problems of RAS, Moscow, Russia;

    Lomonosov Moscow State University, Faculty of Computational Mathematics and Cybernetics, Moscow, Russia;

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