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Reply on Comment on 'High resolution coherence analysis between planetary and climate oscillations' by S. Holm

机译:S. Holm对“行星和气候振荡之间的高分辨率相干分析”的评论答复

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Holm (ASR, 2018) claims that Scafetta (ASR 57, 2121-2135, 2016) is "irreproducible" because I would have left "undocumented" the values of two parameters (a reduced-rank index p and a regularization term 6) that he claimed to be requested in the Magnitude Squared Coherence Canonical Correlation Analysis (MSC-CCA). Yet, my analysis did not require such two parameters. In fact: (1) using the MSC-CCA reduced-rank option neither changes the result nor was needed since Scafetta (2016) statistically evaluated the significance of the coherence spectral peaks; (2) the analysis algorithm neither contains nor needed the regularization term delta. Herein I show that Holm could not replicate Scafetta (2016) because he used different analysis algorithms. In fact, although Holm claimed to be using MSC-CCA, for his Figs. 2-4 he used a MatLab code labeled "gcs_cca_1 D.m" (see paragraph 2 of his Section 3), which Holm also modified, that implements a different methodology known as the Generalized Coherence Spectrum using the Canonical Correlation Analysis (GCS-CCA). This code is herein demonstrated to be unreliable under specific statistical circumstances such as those required to replicate Scafetta (2016). On the contrary, the MSC-CCA method is stable and reliable. Moreover, Holm could not replicate my result also in his Fig. 5 because there he used the basic Welch MSC algorithm by erroneously equating it to MSC-CCA. Herein I clarify step-by-step how to proceed with the correct analysis, and I fully confirm the 95% significance of my results. I add data and codes to easily replicate my results. (C) 2018 COSPAR. Published by Elsevier Ltd. All rights reserved.
机译:Holm(ASR,2018)声称Scafetta(ASR 57,2121-2135,2016)是“不可复制的”,因为我将“未记录”两个参数的值(降阶索引p和正则化项6)他声称是在幅度平方相干典范相关分析(MSC-CCA)中被要求的。但是,我的分析不需要这两个参数。实际上:(1)使用MSC-CCA降秩选项既不会改变结果,也不需要,因为Scafetta(2016)从统计学上评估了相干光谱峰的重要性; (2)分析算法既不包含也不需要正则项增量。在本文中,我证明了霍尔姆无法复制Scafetta(2016),因为他使用了不同的分析算法。实际上,尽管Holm声称使用MSC-CCA,但他的图却是。 2-4,他使用了标有“ gcs_cca_1 D.m”的MatLab代码(请参见他的第3节第2段),Holm也对其进行了修改,该代码使用典型相关分析(GCS-CCA)实现了称为通用相干谱的另一种方法。本文证明此代码在特定的统计情况下是不可靠的,例如复制Scafetta(2016)所需的那些情况。相反,MSC-CCA方法是稳定可靠的。此外,Holm也无法在他的图5中复制我的结果,因为在那儿他错误地将其等同于MSC-CCA而使用了基本的Welch MSC算法。在此,我将逐步阐明如何进行正确的分析,并且完全确认了我的结果具有95%的重要性。我添加数据和代码以轻松复制我的结果。 (C)2018年COSPAR。由Elsevier Ltd.出版。保留所有权利。

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