Testing for long‐range dependence in the presence of shifting means or a slowly declining trend, using a variance‐type estimator
Testing for long‐range dependence in the presence of shifting means or a slowly declining trend, using a variance‐type estimator
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DOI：
10.1111/1467-9892.00050
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发表时间：
1997-05
影响因子：
0.9
通讯作者：
Vadim Teverovsky;M. Taqqu
中科院分区：
文献类型：
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作者：
Vadim Teverovsky;M. Taqqu
在这篇文章中，我们考察了当使用方差型估计时，某些类型的非平稳性对检测长期相关性和估计赫斯特参数H的影响。当序列具有均值跳跃或缓慢趋势时，由此得到的H的估计可能具有误导性。在这种情况下，绘制方差的对数与聚集水平的对数的曲线图会得到一条与直线截然不同的曲线。提出了一种区分长期相关性和非平稳性影响的方法。
In this paper we examine the effects of certain types of non‐ stationarity on the detection of long‐range dependence and on the estimation of the Hurst parameter H, when using a variance‐type estimator. The resulting estimate of H can be misleading when the series has either a jump in the mean or a slow trend. In such a case, plotting the logarithm of the variance versus the logarithm of the level of aggregation gives a curve which is quite different from a straight line. A method for distinguishing between the effects of long‐range dependence and these types of non‐stationarity is developed.