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摘要翻译：
为了研究各种（人工的和现实的）时间序列，MFDFA技术的不同变体被应用。我们的分析表明，计算的奇异谱对MFDFA方法中使用的去中心多项式的阶数非常敏感。计算中所用多项式的阶数与多重分形谱的宽度（以及Hurst指数）之间的关系是明显的。此外，这种关系的类型本身取决于所分析的信号的种类。因此，这样的分析可以给我们提供一些关于所研究的时间序列的相关结构的额外信息。
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英文标题：
《Effect of detrending on multifractal characteristics》
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作者：
P. O\'swi\k{e}cimka, S. Dro\.zd\.z, J. Kwapie\'n and A. Z. G\'orski
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最新提交年份：
2012
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分类信息：
一级分类：Physics 物理学
二级分类：Data Analysis, Statistics and Probability 数据分析、统计与概率
分类描述：Methods, software and hardware for physics data analysis: data processing and storage; measurement methodology; statistical and mathematical aspects such as parametrization and uncertainties.
物理数据分析的方法、软硬件：数据处理与存储；测量方法；统计和数学方面，如参数化和不确定性。
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一级分类：Quantitative Finance 数量金融学
二级分类：Statistical Finance 统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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英文摘要：
Different variants of MFDFA technique are applied in order to investigate various (artificial and real-world) time series. Our analysis shows that the calculated singularity spectra are very sensitive to the order of the detrending polynomial used within the MFDFA method. The relation between the width of the multifractal spectrum (as well as the Hurst exponent) and the order of the polynomial used in calculation is evident. Furthermore, type of this relation itself depends on the kind of analyzed signal. Therefore, such an analysis can give us some extra information about the correlative structure of the time series being studied.
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PDF链接：
https://arxiv.org/pdf/1212.0354
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