Modified multiscale cross-sample entropy for complex time series
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- 作者：Yi Yin ; Pengjian Shang ; pjshangdu@163.com" class="auth_mail" title="E-mail the corresponding author ; Guochen Feng
- 关键词：Refined composite multiscale cross-sample entropy (RCMCSE) ; Composite multiscale cross-sample entropy (CMCSE) ; Multiscale cross-sample entropy (MCSE) ; Artificial time series ; Stock indices
- 刊名：Applied Mathematics and Computation
- 出版年：2016
- 出版时间：20 October 2016
- 年：2016
- 卷：289
- 期：Complete
- 页码：98-110
- 全文大小：1059 K
文摘
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We introduce the CMCSE and further propose the RCMCSE method.
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MCSE, CMCSE and RCMCSE methods are employed to artificial and financial time series.
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RCMCSE reduces standard deviation and the probability of inducing undefined entropy.
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RCMCSE can provide better robustness and more accurate entropies.
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RCMCSE is more applicable for the study between US and Chinese stock markets.