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Activity Number: 510 - New Developments in Time Series Analysis and Change Point Detection
Type: Contributed
Date/Time: Wednesday, August 2, 2017 : 10:30 AM to 12:20 PM
Sponsor: IMS
Abstract #324024
Title: Change Point Estimation in a Dynamic Stochastic Block Model
Author(s): Monika Bhattacharjee* and George Michailidis and Moulinath Banerjee
Companies: Informatics Institute, University of Florida and University of Florida and University of Michigan
Keywords: stochastic block model ; change point ; probability matrix ; clustering ; estimation
Abstract:

We consider a dynamic stochastic block model with single change point. An easily implementable algorithm based on maximum pseudo-likelihood method and spectral clustering is proposed for estimating the change point. We also estimate the edge-probability matrices and clustering functions before and after the change point. The convergence rate and asymptotic distribution for these estimators are discussed and compared with other existing works in the literature. This is joint work with George Michailidis and Moulinath Banerjee.


Authors who are presenting talks have a * after their name.

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