Seminar: Multiple Change-points Estimation by Empirical Bayesian Information Criteria and Gibbs Sampling

SpeakerGuoqi Qian
AffiliationThe University of Melbourne
DateThursday, 04 Jun 2015
Time16:00 - 17:00
Location102, 1-19 Torrington Place, Statistical Science
Event seriesStatistical Science Seminars

We have developed a new method to estimate multiple change-points that may exist in a sequence of observations. The method consists of a specific empirical Bayesian information criterion (emBIC) to assess the fitness and virtue of each candidate configuration of change-points, and also a specific Gibbs sampling induced stochastic search algorithm to find the optimal change-points configuration. It is shown that emBIC can significantly improve over BIC that is known to have tendency of over-detecting multiple change-points.
The use of the stochastic search induced by Gibbs sampling enables one to find the optimal change-points configuration with high probability and without going through an exhaustive search that is mostly computationally infeasible. Simulation studies and real data examples are presented to illustrate and assess the proposed method.

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