The weighted sum of powers in mean for estimating a change point in linear processes with random coefficients.

Let {Xi, 1 ≤ i ≤ n} be a sequence of linear process based on dependent random variables with random coefficients, which has a mean shift at an unknown location. The weighted sum of powers in mean (WSPM, for short) estimator of the change point is proposed. The weak consistency, the rate of weak consistency and strong consistency for the WSPM estimator are established under some mild conditions. Simulation studies and two real data exercises are also provided to show the superiority of this new method to some existing methods.