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Multiresolution diffusion entropy analysis of time series: an application to births to teenagers in Texas

机译:时间序列的多分辨率扩散熵分析:在德克萨斯州青少年出生中的应用

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The multiresolution diffusion entropy analysis is used to evaluate the stochastic information left in a time series after systematic removal of certain non-stationarities. This method allows us to establish whether the identified patterns are sufficient to capture all relevant information contained in a time series. If they do not, the method suggests the need for further interpretation to explain the residual memory in the signal. We apply the multiresolution diffusion entropy analysis to the daily count of births to teens in Texas from 1964 through 2000 because it is a typical example of a non-stationary time series, having an anomalous trend, an annual variation, as well as short time fluctuations. The analysis is repeated for the three main racial/ethnic groups in Texas (White, Hispanic and African American), as well as, to married and unmarried teens during the years from 1994 to 2000 and we study the differences that emerge among the groups. (C) 2003 Elsevier Ltd. All rights reserved.
机译:多分辨率扩散熵分析用于评估系统消除某些非平稳性后在时间序列中留下的随机信息。这种方法使我们能够确定所识别的模式是否足以捕获时间序列中包含的所有相关信息。如果不是,则该方法建议需要进一步解释以解释信号中的剩余内存。我们将多分辨率扩散熵分析应用于1964年至2000年德克萨斯州青少年的每日出生计数,因为它是一个非平稳时间序列的典型示例,具有异常趋势,年度变化以及短时间波动。在1994年至2000年的几年中,对德克萨斯州的三个主要种族/族裔群体(白人,西班牙裔和非裔美国人)以及已婚和未婚青少年进行了重复分析,我们研究了这些群体之间出现的差异。 (C)2003 Elsevier Ltd.保留所有权利。

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