LAUSR

This paper focuses on the issue of detecting the multiple change points for linear processes under negatively super-additive dependence (NSD). We propose a CUSUM-type method in the multiple variance change model and establish the weak convergence rate of the change points estimation. To carry out this method, we give a multiple variance-change iterative (MVCI) algorithm. Additionally, some simulations are implemented to substantiate the validity of the CUSUM-type method. Comparison with some best methods indicates that the CUSUM-type change point estimation is computationally competitive and superior in terms of the mean squared error (MSE).