论文标题
在预测临界过渡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
论文作者
论文摘要
最近的研究表明，从测得的时间序列中提取的指标的趋势可以表明即将过渡。肯德尔的τ系数通常用于研究与关键减慢现象和其他预测关键过渡的方法相关的统计趋势。由于统计数据是根据时间序列估算的，因此肯德尔τ的值受到参数的影响，例如窗口大小，样本率和时间序列的长度，从而在解释结果时遇到挑战和不确定性。在这项研究中，我们研究了不同参数对从肯德尔τ获得的趋势分布的影响，并提供了有关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Kendallτ值的重要性。与传统的参数ARMA测试相比，非参数测试的计算速度要快得多。
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.
