Comparing spectra and coherences for groups of unequal size
Comparing spectra and coherences for groups of unequal size
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DOI：
10.1016/j.jneumeth.2006.07.011
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发表时间：
2007-01-30
影响因子：
3
通讯作者：
Mitra, Partha
中科院分区：
文献类型：
--
作者：
Bokil, Hemant;Purpura, Keith;Mitra, Partha
光谱和相干性是时间序列内部和之间关联的标准度量。这些措施有几个优点，他们的时域同行，而不是最不重要的是能够推导和估计置信区间。然而，比较两组观测的光谱和相干性是一个没有得到太多关注的问题。这个问题在神经科学中很重要，因为确定不同的实验/行为条件下的估计值是否不同通常是非常有趣的。在这里，我们提出了一个解决这个问题的方法。基于谱估计和相干估计的已知分布性质，我们得到了两个谱估计或相干估计相等的检验。该检验适用于样本量不等的情况。我们还推导出了所提出的检验统计量的方差的折刀估计。我们建议，比较从刀切过程中获得的估计与理论估计提供了一个强大的手段，确定是否有问题的数据显示非高斯或非平稳行为。最后，我们提出了应用程序的方法模拟和真实的数据。(c)2006 Elsevier B. V.保留所有权利。
Spectra and coherences are standard measures of association within and between time series. These measures have several advantages over their time-domain counterparts, not the least of which is the ability to derive and estimate confidence intervals. However, comparing spectra and coherences between two groups of observation is a problem that has not received much attention. This problem is important in neuroscience since it is often of great interest to determine whether the estimates differ between distinct experimental/behavioral conditions. Here we propose one approach to this problem. Based on the known distributional properties of spectral and coherence estimates, we derive a test for equality of two spectral or coherence estimates. The test is applicable to unequal sample sizes. We also derive jackknifed estimates of the variance of the proposed test statistic. We suggest that comparing the estimates obtained from the jackknife procedure with the theoretical estimates provides a robust means of determining whether the data in question shows non-Gaussian or non-stationary behavior. Finally, we present applications of the method to simulated and real data. (c) 2006 Elsevier B.V. All rights reserved.