A Note on Online Change Point Detection

06/05/2020
by   Yi Yu, et al.
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Online change point detection is originated in sequential analysis, which has been thoroughly studied for more than half century. A variety of methods and optimality results have been established over the years. In this paper, we are concerned with the univariate online change point detection problem allowing for all model parameters to change. We establish a theoretical framework to allow for more refined minimax results. This includes a phase transition phenomenon and a study of the detection delay under three forms of Type-I error controls. We also examine a common belief on the conservativeness of different Type-I error control strategies and provide results for potentially multiple change points scenarios.

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