Structural Breaks in Time Series

时间序列的结构性断裂

• 批准号: 96458173
• 负责人: Professor Dr. Josef G. Steinebach
• 金额: --
• 依托单位: Abteilung Mathematik
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2008
• 资助国家: 德国
• 起止时间: 2007-12-31 至 2011-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/96458173?language=en
• 关键词: Structural; Breaks; Time; Series

Statistical modelling of trends and changes in time series has attracted many statisticians in the last two decades. The reason is that there is a whole spectrum of applications when data indicate trend(s) or change(s) and as a consequence it also results in a number of interesting theoretical problems.In this project we want to focus on developing techniques for the statistical analysis in series of dependent data (time series), that is to detect structural breaks (change-points) in certain model assumptions via specific testing or monitoring procedures. Since data sets from applications typically do not satisfy certain assumptions of independence or identical distributions, we aim at further developing change-point methods for dependent data. The idea is to modify existing procedures, which have been developed for the independent case, to models possessing certain dependency structures, and taking these specific dependencies into account in the design of the schemes. A further goal is to obtain corresponding theoretical results for multivariate time series, again according to the requirements from applications.

在过去的二十年中，时间序列趋势和变化的统计建模吸引了许多统计学家。原因是，当数据指示趋势或变化时，会出现一系列的应用，因此也会导致许多有趣的理论问题。在这个项目中，我们希望重点开发一系列相关数据（时间序列）的统计分析技术，即通过特定的测试或监控程序来检测某些模型假设中的结构断裂（变化点）。由于来自应用程序的数据集通常不满足某些独立性或相同分布的假设，因此我们的目标是进一步开发相关数据的变点方法。这个想法是将针对独立案例开发的现有程序修改为具有某些依赖性结构的模型，并在方案设计中考虑这些特定的依赖性。进一步的目标是根据应用的要求，获得多元时间序列的相应理论结果。

项目成果

Testing the Equality of Covariance Operators in Functional Samples

• DOI: 10.1111/j.1467-9469.2012.00796.x
• 发表时间: 2011-04
• 期刊: Scandinavian Journal of Statistics
• 影响因子: 1
• 作者: Stefan Fremdt;J. Steinebach;Lajos Horv'ath;P. Kokoszka

Delay time in monitoring jump changes in linear models

• DOI: 10.1080/02331888.2011.577895
• 发表时间: 2013-01
• 期刊: Statistics
• 影响因子: 1.9
• 作者: A. Černíková;M. Hušková;Z. Prášková;J. Steinebach

SEQUENTIAL TESTING FOR THE STABILITY OF HIGH-FREQUENCY PORTFOLIO BETAS

• DOI: 10.1017/s0266466611000673
• 发表时间: 2012-08-01
• 期刊: ECONOMETRIC THEORY
• 影响因子: 0.8
• 作者: Aue, Alexander;Hormann, Siegfried;Steinebach, Josef G.
• 通讯作者: Steinebach, Josef G.