Covariance regularization for metabolomic data on the drought resistance of barley

Adam Mieldzioc, Monika Mokrzycka, Aneta Sawikowska
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引用次数: 3

Abstract

Summary Modern chromatography largely uses the technique of gas chromatography coupled with mass spectrometry (GC–MS). For a set of data concerning the drought resistance of barley, the problem of the characterization of a covariance structure is investigated with the use of two methods. The first is based on the Frobenius norm and the second on the entropy loss function. For the four considered covariance structures – compound symmetry, three-diagonal and penta-diagonal Toeplitz and autoregression of order one – the Frobenius norm indicates the compound symmetry matrix and autoregression of order one as the most relevant, whilst the entropy loss function gives a slight indication in favor of the compound symmetry structure.
大麦抗旱性代谢组学数据的协方差正则化
现代色谱主要采用气相色谱-质谱联用技术(GC-MS)。对于一组有关大麦抗旱性的数据,用两种方法研究了协方差结构的表征问题。第一种是基于Frobenius范数,第二种是基于熵损失函数。对于四种被考虑的协方差结构——复合对称、三对角和五对角Toeplitz和一阶自回归——Frobenius范数表明复合对称矩阵和一阶自回归是最相关的,而熵损失函数给出了有利于复合对称结构的轻微指示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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