Structural Breaks in Time Series

• Applicant: Professor Dr. Josef G. Steinebach
• Subject Area: Mathematics
• Term: from 2008 to 2012
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 96458173

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.

• DFG Programme: Research Grants
• International Connection: Czech Republic
• Participating Person: Professorin Dr. Marie Huskova