右删失数据条件密度函数的非参数估计
Nonparametric Conditional Density Estimation for Right-Censored Data
摘要: 本文考虑响应变量受到随机右删失的回归模型，在右删失数据与未受删失影响数据条件独立的情况下，构造了一种右删失数据条件密度函数的非参数估计量，进而得到该估计量的一致强相合性及其收敛速度，最后通过模拟探究了估计量的估计效果。
Abstract: In this paper, we consider a regression model in which the response is subject to random right censored. Under the assumption that survival time and censored time are conditional independent, we construct a nonparametric conditional density estimator. The uniform strong consistency of the conditional density estimator and its convergence rate are derived. Finally, we study the accuracy of the estimator.
文章引用：薛婧. 右删失数据条件密度函数的非参数估计[J]. 统计学与应用, 2022, 11(5): 1168-1179. https://doi.org/10.12677/SA.2022.115120

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