Mean Change Point Detection Based on Jump Information Criterion
The change-point model has been proved to have practical significance in many fields,in which the mean single change-point model is the basis of the change-point model.This paper mainly focuses on solving the statistical inference problem of whether there is a change point in a single change-point statistical model.For the mean single change-point model,this paper converts the traditional hypothesis testing idea into an estimation problem for the number of variable points to be 0 or 1,thus avoiding the critical value selection problem;the optimization objective function based on the jump information criterion is established,and the consistency of the number of change points and its conver-gence speed are proved,and finally the construction form of the optimal jump information criterion is derived.The numerical experimental results show that our proposed method has superior statistical per-formance compared to existing test-based methods.
mean single change-point modeljump information criterionpenalty itemconsistency
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