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STOR Colloquium: Hao Chen, UC Davis

6 Sep @ 3:30 pm - 4:30 pm

Change-point detection for locally dependent data


Local dependence is common in multivariate and non-Euclidean data sequences, such as network data. We consider the testing and estimation of change-points in such sequences. A new way of permutation, circular block permutation with a randomized starting point, is proposed and studied for a scan statistic utilizing graphs representing the similarity between observations. The proposed permutation approach could correctly address for local dependence and make it possible the theoretical treatments for the non-parametric graph-based scan statistic for locally dependent data. We derive accurate analytic approximations to the significance of graph-based scan statistics under the circular block permutation framework, facilitating its application to locally dependent multivariate or object data sequences.


Refreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall


6 Sep
3:30 pm - 4:30 pm
Event Category:


120 Hanes Hall
Hanes Hall
Chapel Hill, NC 27599 United States