Detrended Correlogram Method for Non-Stationary Time-Series Analysis

被引：3
|
作者：
Zebende, G. F. [1 ]
Guedes, E. F. [2 ]
机构：
[1] Univ Estadual Feira de Santana, Dept Phys, Novo Horizonte, BA, Brazil
[2] Univ Fed Reconcavo Bahia, Ctr Exact Sci & Technol, Cruz Das Almas, BA, Brazil
来源：
FLUCTUATION AND NOISE LETTERS | 2022年 / 21卷 / 02期
关键词：
Correlogram; time series analysis; DCCA cross-correlation coefficient;
D O I：
10.1142/S0219477522500122
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
A correlogram is a statistical tool that is used to check time-series memory by computing the auto-correlation coefficient as a function of the time lag. If the time-series has no memory, then the auto-correlation must be close to zero for any time lag, otherwise if there is a memory, then the auto-correlations must be significantly different from zero. Therefore, based on the robust detrended cross-correlation coefficient, ppccA, we propose the detrended correlogram method in this paper, which will be tested for some time-series (simulated and empirical). This new statistical tool is able to visualize a complete map of the auto-correlation for many time lags and time-scales, and can therefore analyze the memory effect for any time-series.
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页数：8
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