截断样本下最近邻估计的强一致收敛速度  

UNIFORM CONVERGENCE RATE OF THE NEAREST NEIGHBORHOOD DENSITY ESTIMATORS IN THE CASE OF CENSORED DATA

作　　者：游凛峰 

机构地区：[1]复旦大学

出　　处：《应用概率统计》1989年第3期243-251,共9页Chinese Journal of Applied Probability and Statistics

摘　　要：本文用最近邻方法寻找在截断样本下的密度估计,证明它的强收敛性并寻求其收敛速度。在某些截断情况下,本文找到的密度估计的收敛速度不仅达到了最佳并且改进了[4]中的收敛速度。In this paper, we oonsider the N. N. density estimators under censored data, and study their strong convergence and their rates of convergence. For certain particular censoring, it is shown that the rate of convergence of the density estimators not only reaches the optimal but also improves Chai's result.

关 键 词：截断样本 最近邻估计 收敛速度 

分 类 号：O212.2[理学—概率论与数理统计]