Consistent and powerful graph-based change-point test for high-dimensional data.
نویسندگان
چکیده
A change-point detection is proposed by using a Bayesian-type statistic based on the shortest Hamiltonian path, and the change-point is estimated by using ratio cut. A permutation procedure is applied to approximate the significance of Bayesian-type statistics. The change-point test is proven to be consistent, and an error probability in change-point estimation is provided. The test is very powerful against alternatives with a shift in variance and is accurate in change-point estimation, as shown in simulation studies. Its applicability in tracking cell division is illustrated.
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ورودعنوان ژورنال:
- Proceedings of the National Academy of Sciences of the United States of America
دوره 114 15 شماره
صفحات -
تاریخ انتشار 2017