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A test for second-order stationarity of a time series based on the discrete Fourier transform

机译:基于离散傅立叶变换的时间序列二阶平稳性检验

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We consider a zero mean discrete time series, and define its discrete Fourier transform (DFT) at the canonical frequencies. It can be shown that the OFT is asymptotically uncorrelated at the canonical frequencies if and only if the time series is second-order stationary. Exploiting this important property, we construct a Portmanteau type test statistic for testing stationarity of the time series. It is shown that under the null of stationarity, the test statistic has approximately a chi-square distribution. To examine the power of the test statistic, the asymptotic distribution under the locally stationary alternative is established. It is shown to be a generalized non-central chi-square, where the non-centrality parameter measures the deviation from stationarity. The test is illustrated with simulations, where is it shown to have good power.
机译:我们考虑零均值离散时间序列,并在标准频率下定义其离散傅里叶变换(DFT)。可以证明,当且仅当时间序列为二阶平稳时,OFT才在标准频率上渐近不相关。利用此重要属性,我们构建了Portmanteau类型的测试统计量,以测试时间序列的平稳性。结果表明,在平稳性为零的情况下,检验统计量近似具有卡方分布。为了检验检验统计量的功效,建立了局部平稳替代项下的渐近分布。它显示为广义的非中心卡方,其中非中心参数用于度量与平稳性的偏差。该测试通过仿真进行了说明,在此表明它具有良好的性能。

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