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On the power of Portmanteau serial correlation tests

机译:关于Portmanteau序列相关测试的强大功能

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This paper studies properties of the portmanteau statistic proposed by Box and Pierce and its modification of Ljung and Box. We show that these portmanteau statistics are feasible analogs to optimal tests for the class of statistics which are linear combinations of consistent estimates of serial correlations. We find, however, that for sample sizes commonly encountered in practice, the efficiency loss in power of portmanteau statistics relative to optimal tests can be substantial, although their size properties are broadly comparable. Our results indicate that tests based on some other non-optimal weighting schemes, including tests with optimal weights constructed from moderately misspecified alternatives, deliver tests with better power than the Box-Pierce or Ljung-Box statistics.
机译:本文研究了Box和Pierce提出的Portmanteau统计量的性质及其对Ljung和Box的修改。我们表明,这些Portmanteau统计信息是最佳的统计类别检验的可行类似物,这些统计数据是序列相关性的一致估计的线性组合。但是,我们发现,对于实践中通常遇到的样本数量,尽管最佳样本的大小属性具有大致可比性,但Portmanteau统计数据相对于最佳测试的效率损失可能是巨大的。我们的结果表明,基于其他一些非最佳加权方案的检验(包括具有由适度错误指定的替代方案构成的最佳权重的检验)所提供的检验的功效要优于Box-Pierce或Ljung-Box统计数据。

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