在预测临界转变的背景下使用肯德尔τ的实用指南
Practical Guide of Using Kendall's τ in the Context of Forecasting Critical Transitions
摘要：
最近的研究表明，从计量的时间序列中提取的指标趋势可以表明过渡即将到来。Kendall τ系数常用于研究与临界慢化现象有关的统计量的趋势以及预测临界转变的其他方法。由于统计数据是从时间序列中估计的，因此肯德尔τ的值受到窗口大小、采样率和时间序列长度等参数的影响，从而导致解释结果的挑战和不确定性。在这项研究中，我们研究了不同参数对从Kendall τ得到的趋势分布的影响，并提供了如何选择这些参数的见解。我们还建议使用非参数Mann-Kendall检验来评估Kendall τ值的显著性。与传统的参数ARMA检验相比，非参数检验的计算速度要快得多。
英文摘要：
Recent studies demonstrate that trends in indicators extracted from measured time series can indicate approaching to an impending transition. Kendall's τ coefficient is often used to study the trend of statistics related to the critical slowing down phenomenon and other methods to forecast critical transitions. Because statistics are estimated from time series, the values of Kendall's τ are affected by parameters such as window size, sample rate and length of the time series, resulting in challenges and uncertainties in interpreting results. In this study, we examine the effects of different parameters on the distribution of the trend obtained from Kendall's τ, and provide insights into how to choose these parameters. We also suggest the use of the non-parametric Mann-Kendall test to evaluate the significance of a Kendall's τ value. The non-parametric test is computationally much faster compared to the traditional parametric ARMA test.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
