A Data-driven Change-point Estimator

Published 23 Oct 2020 in stat.AP, math.ST, and stat.TH | (2010.12449v1)

Abstract: The q-weighted CUSUM and their corresponding estimator are well known statistics for change-point detection and estimation. They have the difficulty that the performance is highly dependent on the location of the change. An adaptive estimator with data-driven weights is presented to overcome this problem, and it is shown that the corresponding adaptive change-point tests are valid.

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Stefanie Schwaar

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