Abstract:
Let Fn and Gn denote the Kaplan-Meier product-limit estimators of lifetime distributions based on two independent samples, and let Fninv and Gninv denote their quantile functions. We consider the corresponding P-P plot Fn(Gninv) and Q-Q plot Fninv(Gn), and establish strong approximations of empirical processes based on these P-P and Q-Q plots by appropriate sequences of Gaussian processes. It is shown that the rates of approximation we obtain are the best which can be achieved by this method. We apply these results to obtain the limiting distributions of test statistics which are functionals of Fn(Gninv(s)) - s, Gn(Fninv(s)) - s, and Fn(Gninv(s)) + Gn(Fninv(s)) - 2s, and propose solutions to the problem of testing the assumption that the underlying lifetime distributions F and G are equal, in the case where the censoring distributions are arbitrary and unknown.