Abstract

Long-term (multiyear) series of biological data have some specific features. The analysis of such data is treated as a statistical problem of the extraction of long-term signal from the general variance, which is determined by a complex of factors. An attempt is made to systematize the key points that should be considered in this problem. The main sources of data variability are considered, including the temporal and spatial variability of various scales and methodical and statistical sources. The methodological approaches to the assessment of these effects and the corresponding data correction are briefly discussed. This requires careful and reasoned data preparation and the choice of the appropriate statistical model and analytical methods. Some of these approaches are illustrated by case studies. However, the problem is too complex to have a single, universal solution that is suitable for any situation.

中文翻译：

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长期生物数据序列分析：方法学问题和可能的解决方案

摘要

长期（多年）生物数据系列具有某些特定特征。此类数据的分析被视为从一般方差中提取长期信号的统计问题，这是由多种因素决定的。试图系统化此问题中应考虑的关键点。考虑了数据可变性的主要来源，包括各种规模的时间和空间可变性以及方法和统计来源。简要讨论了评估这些影响和相应数据校正的方法学方法。这就需要仔细和合理的数据准备，以及选择适当的统计模型和分析方法。案例研究说明了其中一些方法。然而，