Schimmel M
Department of Geophysics, University of Sao Paulo, Brazil.
Biol Rhythm Res. 2001 Jul;32(3):355-60. doi: 10.1076/brhm.32.3.355.1346.
With respect to the first example in Schimmel (2001), Van Dongen et al. (2001) conclude from their Lomb-Scargle analysis that the noise I used 'contains new periodicities that are added to the signal (these periodicities by themselves resemble a harmonic series of a 38-hour rhythm).' They infer that 'the variance of the added noise is about five times as large as the variance of the signal' causing the detection of the new significant periodicities in the noise prior to the 24-h bimodal rhythm. Moreover the 'example reflects a combination of an extremely non-sinusoidal signal with noise that is not independent, which results in a time series that is difficult to analyze with virtually any know method.' In the following, I briefly examine these concerns to avoid misunderstandings and to alert that with an adequate use of the statistical significance test, misleading conclusions can be obtained. Although this paper further emphasizes difficulties in the detection with Lomb-Scargle periodograms, this should not be used as de-motivation. As stated in Schimmel (2001) Lomb-Scargle is a powerful technique but such as any other method one should be aware about its limitations, and use additional tools to constrain the true data characteristics.
关于施密尔(2001年)的第一个例子,范·东根等人(2001年)通过他们的 Lomb-Scargle 分析得出结论,认为我所使用的噪声“包含添加到信号中的新周期(这些周期本身类似于38小时节律的谐波序列)”。他们推断“添加噪声的方差约为信号方差的五倍”,这导致在24小时双峰节律之前就检测到了噪声中的新显著周期。此外,“该例子反映了一个极其非正弦信号与非独立噪声的组合,这导致了一个几乎用任何已知方法都难以分析的时间序列”。在下文中,我将简要探讨这些问题,以避免误解,并提醒大家,即使充分使用统计显著性检验,也可能得出误导性结论。尽管本文进一步强调了使用 Lomb-Scargle 周期图进行检测时存在的困难,但这不应该成为消极对待的理由。正如施密尔(2001年)所述,Lomb-Scargle 是一种强大的技术,但与任何其他方法一样,人们应该意识到它的局限性,并使用其他工具来确定真实的数据特征。