EMPIRICAL LIKELIHOOD CONFIDENCE INTERVALS FOR DEPENDENT DURATION DATA
针对删失相依数据，基于渐近正态、经验似然和分块经验似然三种方法构建生存分布泛函的置信区间，并通过模拟评估其表现。
Three types of confidence intervals are developed for a general class of functionals of a survival distribution based on censored dependent data. The confidence intervals are constructed via asymptotic normality (Wald’s method), the empirical likelihood (EL) method, and the blockwise EL method in which sample means over blocks of observations are used in place of the original data. Asymptotic results are derived to accurately calibrate the various procedures, and their performance is evaluated in a simulation study. The problem of the choice of the block size is also discussed.