摘要
在删失数据的模型下，对于光滑未知的分布函数Ｆ０，文中提出了光滑化的方法去估计Ｆ０，得到了光滑ＰＬ估计Ｆｎ，并建立了Ｆｎ在Ｄ（－∞，Ｔ），Ｔ＜ＴＦ上的弱收敛和强相合的结果．同时也获得了光滑ＰＬ过程的强逼近和重对数律．
Weak convergence and strong consistency are established for a smooth version of the classical product-limit estimator of a distribution function when the data are subject to random censorship. The weak convergences oil D(I) = D(-∞,T] for T < TF=inf{x: F(x)=1} are shown to hold for the entire interval I under basically the same assumptions that have been used in the literature to establish the weak convergence of normalized estimator in D(I). Moreover,strong approximations and the laws of the iterated logarithm are proved.
出处
《数学学报（中文版）》
SCIE
CSCD
北大核心
1996年第2期238-246,共9页
Acta Mathematica Sinica：Chinese Series
基金
国家自然科学基金
关键词
重对数律
光滑PL过程
乘积限估计
渐近性
weak convergence, strong approximation, product-limit estimator, kernel smooth,law of the iterated logarithm
