Estimation of Conditional Jointly Survival Function Under Dependent Right Random Censored Data

The problem consist in estimation of conditional jointly survival function by right random censored observations in the presence of covariate. We propose two estimators of conditional jointly survival function and study its large sample properties. We show an asymptotic equivalence of estimators. We derive an almost sure representation results for estimators. Also, present result of asymptotic normality with tending to the same limiting Gaussian process.

Automated summary

The problem addressed in this article is the estimation of the conditional joint survival function using right random censored observations in the presence of covariate. Two estimators of the conditional joint survival function are proposed, and their large sample properties are studied. The authors demonstrate the asymptotic equivalence of the estimators and derive almost sure representation results. Additionally, the article presents results of asymptotic normality with convergence to the same limiting Gaussian process.