基于BCUSUM的多参数变点估计OA北大核心CHSSCDCSSCICSTPCD

This paper investigates the detection method of multi-parameter change points in regression model based on the inverse order characteristics of recursive residuals and isolate-detect.Firstly,the regression model with change points is con-structed.In view of the fact that the multivariate forward CUSUM test prevents the loss of power when the mean of the covariates is orthogonal to the offset,but that its change point detection effect is not ideal,the modified test statistic BCUSUM(Backward Cu-mulative Sum)is introduced.Secondly,with the fast and efficient isolate-detect technology combined,a MCPDP(Multiple Change Points Detection of Parameter)algorithm is proposed to estimate the number and corresponding positions of change points.Finally,the simulation results show that the proposed method can control the test level well and has higher power.The evaluation results show that the MCPDP algorithm has better performance of change point estimation.The case analysis shows that the traffic flow change points are consistent with the actual traffic situations,which verifies the effectiveness of the method.The model construct-ed in this paper can be used as a modification of the deterministic empirical relationship of traffic parameters.