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Testing nonstationary time series for Gaussianity and linearity using the evolutionary bispectrum: An application to internet traffic data

机译:使用进化双谱测试高斯和线性度的非平稳时间序列:对互联网流量数据的应用

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We propose statistical tests for Gaussianity and linearity of nonstationary time series based on the evolutionary bispectrum. These tests can be applied to a particular subclass of nonstationary processes, the so-called oscillatory or slowly varying. We run some simulated examples and examine the power of the tests. Then we apply these tests to time series of network measurements arising from internet traffic, processes which have been demonstrated by several researchers to be typically nonstationary. We also address the question of whether such processes can be described by some model whose parameters vary with time. We show that there is evidence of non-Gaussianity and nonlinearity in such processes under the assumption that they are described by a model whose parameters (and so its spectral characteristics) vary slowly with time.
机译:我们提出了基于进化双谱的非平稳时间序列的高斯和线性度的统计检验。这些测试可以应用于非平稳过程的特定子类,即所谓的振荡或缓慢变化。我们运行一些模拟示例,并检验测试的功效。然后,我们将这些测试应用于由互联网流量引起的网络测量的时间序列,该过程已被一些研究人员证明通常是不稳定的。我们还解决了这样的问题:是否可以通过参数随时间变化的某些模型来描述此类过程。我们表明,在这样的过程中存在非高斯性和非线性的证据,假设它们是由模型描述的,其参数(及其光谱特性)随时间缓慢变化。

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