Resumen de A change-point problem in relative error-based regression

Zhanfeng Wang, Wenxin Liu, Yuanyuan Lin

• A nonparametric relative error-based method is proposed to detect and estimate the change point for the multiplicative regression models. The asymptotic distribution of the proposed test statistic for no change-point effect is established. We prove the n-consistency of the proposed estimator of the change point. Simulation studies demonstrate that change-point detection and estimation with relative errors perform reasonably well in many practical situations. Application is illustrated with a financial dataset.