Change-Point Detection in Time Series
Program Director UROP
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- Project Offer-Number:
- UROP International, RWTH UROP
- Organisation unit:
- Chair of Stochastics and Institute of Statistics
- Language Skills:
- English or German
- Computer Skills:
- Programming skills, preferably in C and R.
Present day data sets are usually dependent time series streams which arrive sequentially, e.g. when monitoring data from financial markets, environmental data or digitized signals in engineering. There is great interest to detect structural changes in such time series in order to trigger measurements such as risk adjustments of financial positions, an alarm when monitoring for biosurveillance or switching to another channel with a lower data transfer rate when transmitting data through a multiplex channel. It is of great interest to study and compare the power of detection procedures to detect various kinds of changes in a data stream.
After reading paper(s) and related material, the task is to implement, test and analyze detection methods we are studying in our group. Implementations and simulations will be done in R and P, respectively. P is our HPC compiler for R with extensions for parallel programming.
Background in probability theory/statistics and basic knowledge of time series models. Knowledge of nonparametric statistics would be