Abstract：This paper improves the condition of window size in paper[ 1 ] ,and obtains the strong consistency of the curisive kernel estimator of m(x)under randomly censored data using the synthetic data method. The condition on window size hn and kernel function k(x)are consistent w ith those under the complete sample case.
赵 霞 周观珍. 随机删失场合基于 Synthetic Data 的回归 函数核估计的强相合性
[J]. 浙江大学学报（理学版）, 1998, 25(4): 1-6.
Zhao Xia Zhou Guanzhen. Regression Function Kernel Estimation Based on Synthetic Data under Random Censorship
. Journal of ZheJIang University(Science Edition), 1998, 25(4): 1-6.
