Journal of Data Science

Abstract: For estimating bivariate survival function under random censor ship, it is commonly believed that the Dabrowska estimator is among the best ones while the Volterra estimator is far from being computational ef ficiency. As we will see, the Volterra estimator is a natural extension of the Kaplan-Meier estimator to bivariate data setting. We believe that the computational ‘inefficiency’ of the Volterra estimator is largely due to the formidable computational complexity of the traditional recursion method. In this paper, we show by numerical study as well as theoretical analysis that the Volterra estimator, once computed by dynamic programming technique, is more computationally efficient than the Dabrowska estimator. Therefore, the Volterra estimator with dynamic programming would be quite recom mendable in applications owing to its significant computational advantages.