Comparative Analysis of Data Dynamics Based on Wavelet Coherence Using Higher-Order Moments
Yasser Mohammad Al-Sharo, Amer Tahseen Abu-Jassar, Oleg Vasiurenko, Vyacheslav V. Lyashenko · 2023
The article addresses the challenges of analyzing data represented as time series, depicting the evolution of a specific process, phenomenon, or object over time. Special emphasis is placed on conducting a comparative analysis of the dynamics among different data sets; so, to achieve this, a method for estimating wavelet coherence is employed. The approach includes transforming the original data through a sliding sampling window using higher-order moments to capture the memory effect. This methodology enables the assessment of dynamics in extensive data sets, thereby enhancing the efficiency of processing and analysis. The article presents results based on real data, providing an additional evaluation of their mutual dynamics. The findings affirm the reliability and effectiveness of such an analysis.