Scandinavian journal of statistics vol:27 issue:3 pages:501-519
A non-parametric wavelet based estimator is proposed for the location of a change-point in an otherwise smooth hazard function under non-informative random right censoring. The proposed estimator is based on wavelet coefficients differences via an appropriate parametrization of the time-frequency plane. The study of the estimator is facilitated by the strong representation theorem for the Kaplan-Meier estimator established by Lo and Singh (1986). The performance of the estimator is checked via simulations and two real examples conclude the paper.