Nonparametric estimation of the bivariate survival function for one modified form of current-status data
In this article, the estimation of the bivariate survival function for one modified form of current-status data is considered. Two types of estimators, which are generalizations of the estimators by Campbell and Foldes [G. Campbell and A. Foldes, Large sample properties of nonparametric statistical inference, in Nonparametric Statistical Inference, B.V. Gnredenko, M.L. Puri, and I. Vineze, eds., North-Holland, Amsterdam, 1982, pp. 103-122] and Dabrowska [D.M. Dabrowska, Kaplan-Meier estimate on the plane, Ann. Stat. 18 (1988), pp. 1475-1489; D.M. Dabrowska, Kaplan-Meier estimate on the plane: weak convergence, LIL, and the bootstrap, J. Multivariate Anal. 29 (1989), pp. 308-325], are proposed. The consistency of the proposed estimators is established. A simulation study is conducted to investigate the performance of the proposed estimators.
bivariate distribution left-censoring right-censoring