Change Point Detection in Length-Biased Weibull Distribution for Random Censored Data Based on Modified Information Criterion

In this article, we study the change point problem of length-biased Weibull distribution under the scenario of random censorship. We construct the likelihood functions of the random censored length-biased Weibull data. We develop a procedure to detect changes in two parameters simultaneously based on a modified information criterion. Simulations are conducted to show the performance of the proposed methods under different settings. We apply the proposed methods to the Channing House data and locate the positions of the change points.