| 缺失数据下的线性泛函的半参数降维推断 |
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| 引用本文： | 祝丽萍,邵伟.缺失数据下的线性泛函的半参数降维推断[J].山东大学学报(理学版),2011,46(4):17-22. |
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| 作者姓名： | 祝丽萍 邵伟 |
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| 作者单位： | 1. 山东大学数学学院,山东济南250100;昌吉学院数学系,新疆昌吉831100
2. 山东大学数学学院,山东济南,250100 |
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| 基金项目： | 新疆维吾尔自治区高校青年教师科研启动基金资助项目(XJEDU2008563) |
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| 摘 要： | 针对缺失数据下线性泛函估计中存在的非参数高维问题和模型参数化后的稳健性问题,提出了线性泛函估计的半参数降维推断方法,通过非参数函数估计来插补线性泛函,井用参数工作函数来降维.所得半参数降维估计具有双稳健的特点,即只要选择概率函数正确参数化或者降维插补指标可以修复线性函数的条件期望,所得估计就是相合的,而且二者都满足时,估计达到最优.
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| 关 键 词： | 线性泛函 缺失数据 降维 |
Linear functionals semi-parametric dimension reduction inference with missing data |
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| ZHU Li-ping
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SHAO Wei.Linear functionals semi-parametric dimension reduction inference with missing data[J].Journal of Shandong University,2011,46(4):17-22. |
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| Authors: | ZHU Li-ping SHAO Wei |
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| Institution: | ZHU Li-ping1,2,SHAO Wei1(1.School of Mathematics,Shandong University,Jinan 250100,Shandong,China,2.Department of Mathematics,Changji College,Changji 831100,Xinjiang,China) |
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| Abstract: | A semi-parametric dimension reduction method is proposed to reconcile the nonparametric regression approach and the model-based approaches in estimating linear functionals with missing data.The linear functionals are estimated through nonparametric functionals estimation,where the dimension is reduced by a parametric working index.The proposed estimator is robust to model misspecification: it is always consistent in that either the selected probability is correctly specified or the working index can recover... |
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| Keywords: | linear functionals missing data dimension reduction |
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