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响应变量随机删失时函数型非参数分位数回归模型的估计
Estimation of nonparametric quantile regression model for functional data with censored response at random
【摘要】 文章在响应变量随机删失时,研究了函数型非参数分位数回归模型,通过极小化逆概率加权分位数损失函数,构造模型中未知非参数函数的估计量。在一定的条件下,获得估计量的渐近正态性;通过模拟研究,验证了估计量的有效性。
【Abstract】 In this paper, the nonparametric quantile regression model is presented to characterize the association between censored survival time and a set of functional predictors when response variables are censored at random, and estimates of nonparametric functions are obtained by minimizing the inverse probability weighted quantile loss function. Under some mild conditions, the asymptotic normality of the estimates is given. Simulation studies further verify the validity of the proposed model.
【关键词】 函数型数据分析(FDA);
分位数回归;
随机删失;
逆概率加权;
渐近正态;
【Key words】 functional data analysis(FDA); quantile regression; censoring at random; inverse probability weighting; asymptotic normal;
【Key words】 functional data analysis(FDA); quantile regression; censoring at random; inverse probability weighting; asymptotic normal;
【基金】 国家自然科学基金资助项目(72071068)
- 【文献出处】 合肥工业大学学报(自然科学版) ,Journal of Hefei University of Technology(Natural Science) , 编辑部邮箱 ,2023年05期
- 【分类号】O212.1
- 【下载频次】23