英文标题：
《Compounding approach for univariate time series with non-stationary
variances》
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作者：
Rudi Sch\\\"afer, Sonja Barkhofen, Thomas Guhr, Hans-J\\\"urgen
St\\\"ockmann, Ulrich Kuhl
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最新提交年份：
2015
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英文摘要：
A defining feature of non-stationary systems is the time dependence of their statistical parameters. Measured time series may exhibit Gaussian statistics on short time horizons, due to the central limit theorem. The sample statistics for long time horizons, however, averages over the time-dependent parameters. To model the long-term statistical behavior, we compound the local distribution with the distribution of its parameters. Here we consider two concrete, but diverse examples of such non-stationary systems, the turbulent air flow of a fan and a time series of foreign exchange rates. Our main focus is to empirically determine the appropriate parameter distribution for the compounding approach. To this end we have to estimate the parameter distribution for univariate time series in a highly non-stationary situation.
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中文摘要：
非平稳系统的一个决定性特征是其统计参数的时间依赖性。由于中心极限定理，测量的时间序列可能在短时间范围内呈现高斯统计。然而，长时间范围内的样本统计在时间相关参数上是平均值。为了模拟长期的统计行为，我们将局部分布与其参数分布相结合。在这里，我们考虑两个具体但不同的非平稳系统的例子，风扇的湍流和外汇汇率的时间序列。我们的主要重点是根据经验确定复合方法的适当参数分布。为此，我们必须在高度非平稳的情况下估计单变量时间序列的参数分布。
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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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