| 模型中协变量部分缺失情况下参数的极大似然估计 |
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| 引用本文： | 许林. 模型中协变量部分缺失情况下参数的极大似然估计[J]. 长春大学学报, 2007, 0(8) |
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| 作者姓名： | 许林 |
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| 作者单位： | 长春大学理学院 吉林长春130022 |
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| 摘 要： | 研究了Cox比例风险模型中协变量部分缺失参数的极大似然估计问题。在实际问题中特别是对生存分析的研究中,数据经常会出现删失、截断、缺失的情况。如何利用这部分不完整的数据信息和参数的约束信息对于实际问题来说是具有意义的。这样可以提高分析的精度,并节省试验费用。本文利用EM算法得到了数据部分缺失参数的极大似然估计。
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| 关 键 词： | Cox比例风险模型 EM算法 极大似然估计 |
Maximum likelihood extimation under linear inequality restrictions in Cox Proportional Hazards Model with missing covariates |
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| XU Lin. Maximum likelihood extimation under linear inequality restrictions in Cox Proportional Hazards Model with missing covariates[J]. Journal of Changchun University, 2007, 0(8) |
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| Authors: | XU Lin |
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| Abstract: | This paper discusses maximum likelihood estimation in Cox Proportional Hazards Model under linear inequality restrictions with missing covariates.In practice,censored data,truncted data and missing data are often encountered with.It is useful to use the incomplete data information and restriction information of parameters.This paper uses EM algorithm and constrained optimation algorithm to obtain the maximum likelihood estimates under linear inequality restrictions with missing data. |
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| Keywords: | Cox Proprotional Hazards Model EM algorithm maximum likelihood estimation |
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