A test for second-order stationarity and approximate confidence intervals for localized autocovariances for locally stationary time series
A test for second-order stationarity and approximate confidence intervals for localized autocovariances for locally stationary time series
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DOI：
10.1111/rssb.12015
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发表时间：
2013-11-01
影响因子：
5.8
通讯作者：
Nason, Guy
中科院分区：
文献类型：
--
作者：
Nason, Guy
许多时间序列不是二阶平稳的，不适合用为平稳序列设计的方法来分析它们。本文介绍了一种新的二阶平稳性检验方法，它可以检测出不同于基于傅立叶方法的平稳性的各种偏离。新的测试在计算上也很快，设计用于处理高斯和大范围的非高斯时间序列，并可以定位时间和尺度上的非平稳性。在地震、爆炸、婴儿心电和模拟时间序列上进行了检验，显示出不同程度的平稳性。第二个主要贡献给出了局部平稳序列的时变自协方差的近似置信度区间，因为为平稳序列计算的通常频带是不合适的。我们的新波段使从业者能够在统计上评估时变自协方差，并在爆炸和模拟时间序列的局部自协方差上展示。
Many time series are not second order stationary and it is not appropriate to analyse them by using methods designed for stationary series. The paper introduces a new test for second-order stationarity that detects kinds of departures from stationarity that are different from those based on Fourier methods. The new test is also computationally fast, designed to work with Gaussian and a wide range of non-Gaussian time series, and can locate non-stationarities in time and scale. The test is demonstrated on earthquake, explosion, infant electrocardiogram and simulated time series showing varying degrees of stationarity. The second main contribution develops approximate confidence intervals for time varying autocovariances for locally stationary series as the usual bands computed for stationary series are not appropriate. Our new bands enable practitioners to assess time varying autocovariances statistically and are exhibited on localized autocovariances of explosion and simulated time series.