Kernel density and hazard rate estimation for censored data under α-mixing condition
Kernel density and hazard rate estimation for censored data under α-mixing condition
复制标题
DOI：
10.1023/a:1016157519826
复制
发表时间：
2002-03-01
影响因子：
1
通讯作者：
Liebscher, E
中科院分区：
文献类型：
--
作者：
Liebscher, E
We derive rates of uniform strong convergence for kernel density estimators and hazard rate estimators in the presence of right censoring. It is assumed that the failure times (survival times) form a stationary a-mixing sequence. Moreover, we show that, by an appropriate choice of the bandwidth, both estimators attain the optimal strong convergence rate known from independent complete samples. The results represent an improvement over that of Cai's paper.
